ALBERT

Description: 〈p〉Publication date: Available online 8 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): K.T. Huynh〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We are interested in the stochastic modeling of a condition-based maintained system subject to continuous deterioration and maintenance actions such as inspection, partial repair and replacement. The partial repair is assumed dependent on the past in the sense that it cannot bring the system back into a deterioration state better than the one reached at the last repair. Such a past-dependency can affect (〈em〉i〈/em〉) the selection of a type of maintenance actions, (〈em〉ii〈/em〉) the maintenance duration, (〈em〉iii〈/em〉) the deterioration level after a maintenance, and (〈em〉iv〈/em〉) the restarting system deterioration behavior. In this paper, all these effects are jointly considered in an unifying condition-based maintenance model on the basis of restarting deterioration states randomly sampled from a probability distribution truncated by the deterioration levels just before a current repair and just after the last repair/replacement. Using results from the semi-regenerative theory, the long-run maintenance cost rate is analytically derived. Numerous sensitivity studies illustrate the impacts of past-dependent partial repairs on the economic performance of the considered condition-based maintained system.〈/p〉〈/div〉

Description: In this manuscript, we define generalized Kincses-Totik type contractions within the context of metric space and consider the existence of a fixed point for such operators. Kincses-Totik type contractions extends the renowned Banach contraction mapping principle in different aspects. First, the continuity condition for the considered mapping is not required. Second, the contraction inequality contains all possible geometrical distances. Third, the contraction inequality is formulated for some iteration of the considered operator, instead of the dealing with the given operator. Fourth and last, the iteration number may vary for each point in the domain of the operator for which we look for a fixed point. Consequently, the proved results generalize the acknowledged results in the field, including the well-known theorems of Seghal, Kincses-Totik, and Banach-Caccioppoli. We present two illustrative examples to support our results. As an application, we consider an Ulam-stability of one of our results.

Description: We propose a derivative free one-point method with memory of order 1.84 for solving nonlinear equations. The formula requires only one function evaluation and, therefore, the efficiency index is also 1.84. The methodology is carried out by approximating the derivative in Newton’s iteration using a rational linear function. Unlike the existing methods of a similar nature, the scheme of the new method is easy to remember and can also be implemented for systems of nonlinear equations. The applicability of the method is demonstrated on some practical as well as academic problems of a scalar and multi-dimensional nature. In addition, to check the efficacy of the new technique, a comparison of its performance with the existing techniques of the same order is also provided.

Description: In this short note we give an elementary description of the linear part of the minimal free resolution of a Stanley-Reisner ring of a simplicial complex Δ . Indeed, the differentials in the linear part are simply a compilation of restriction maps in the simplicial cohomology of induced subcomplexes of Δ . Along the way, we also show that if a monomial ideal has at least one generator of degree 2, then the linear strand of its minimal free resolution can be written using only ± 1 coefficients.

Description: In this paper, we propose a branch-and-bound algorithm to solve exactly the minimum vertex cover (MVC) problem. Since a tight lower bound for MVC has a significant influence on the efficiency of a branch-and-bound algorithm, we define two novel lower bounds to help prune the search space. One is based on the degree of vertices, and the other is based on MaxSAT reasoning. The experiment confirms that our algorithm is faster than previous exact algorithms and can find better results than heuristic algorithms.

Description: We present fixed points results of multivalued Prešić type k-step iterative mappings satisfying generalized weakly contraction conditions in metric spaces. An example is presented to support the main result proved herein. The stability of fixed point sets of multivalued Prešić type weakly contractive mappings are also established. Global attractivity result for the class of matrix difference equations is derived as application of the result presented herein. These results generalize and extend various comparable results in the existing literature.

Description: 〈p〉Publication date: Available online 5 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Shichen Zhang, Jianxiong Zhang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Nowadays, some suppliers are looking for offline expansion in addition to their preexisting online channels relying on e-tailers. This study focuses on the e-tailer’s demand information sharing strategy with the supplier who may build upon brick-and-mortar stores. Both prevailing agreements between the supplier and the e-tailer are investigated: agency selling and reselling. The equilibrium results are quite different under these two agreements. Specifically, when the supplier’s offline entry cost is very small or large, the e-tailer shares information under agency selling while keeps information private under reselling. When the entry cost is intermediate, channel substitution rate is large and information uncertainty is small, the e-tailer withholds the demand information under agency selling while shares information under reselling to deter the supplier from entering an offline channel. Furthermore, two extensions about consumer behavior in multichannel selection are discussed: showrooming and webrooming. With showrooming or webrooming, the e-tailer’s information sharing decisions qualitatively hold, while with showrooming the drive factor behind may change; that is, withholding information under agency selling and sharing information under reselling may also serve as measures to encourage supplier offline entry when the effect of showrooming is strong.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 2 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Kieran Conboy, Patrick Mikalef, Denis Dennehy, John Krogstie〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉While the topic of analytics is rapidly growing in popularity across various domains, there is still a relatively low amount of empirical work in the field of operations research (OR). While studies of various technical and business aspects of analytics are emerging in OR, little has been done to address how the OR community can leverage business analytics in dynamic and uncertain environments – the very place where OR is supposed to play a key role. To address this gap, this study draws on the dynamic capabilities view of the firm and builds on eight selected case studies of operations research activity in large organisations, each of which have invested significantly in analytics technology and implementation. The study identifies fourteen analytics-enabled micro-foundations of dynamic capabilities, essentially highlighting how organisations can use analytics to manage and enhance their OR activities in dynamic and uncertain environments. This study also identifies six key cross-cutting propositions emerging from the data and develops a roadmap for future OR researchers to address these issues and improve the use and value of analytics as enablers of organisational dynamic capabilities.〈/p〉〈/div〉

Description: 〈p〉Publication date: 1 December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research, Volume 279, Issue 2〈/p〉 〈p〉Author(s): 〈/p〉

Description: In the year 2004, Chang and Teng investigated an inventory model for deteriorating items in which the supplier not only provides a cash discount, but also allows a permissible delay in payments. The main purpose of the present investigation is three-fold, as follows. First, it is found herein that Theorem 1 of Chang and Teng (2004) has notable shortcomings in terms of their determination of the optimal solution of the annual total relevant cost Z ( T ) by adopting the Taylor-series approximation method. Theorem 1 in this paper does not make use of the Taylor-series approximation method in order to overcome the shortcomings in Chang and Teng (2004) and alternatively derives all the optimal solutions of the annual total relevant cost Z ( T ) . Secondly, this paper systematically revisits the annual total relevant cost Z ( T ) in Chang and Teng (2004) and presents in detail the mathematically correct ways for the derivations of Z ( T ) . Thirdly, this paper not only shows that Theorem 1 of Chang and Teng (2004) is not necessarily true for finding the optimal solution of the annual total relevant cost Z ( T ) , but it also demonstrates how Theorem 1 in this paper can locate all of the optimal solutions of Z ( T ) . The mathematical analytic investigation presented in this paper is believed to be useful for correct managerial considerations and managerial decisions.

Description: This paper characterizes the retailer’s loss aversion by introducing a loss aversion coefficient and proposes a new loss aversion utility function for the retailer. To hedge against the risk arising from the uncertain market demand, we use the Conditional Value-at-Risk (CVaR) measure to quantify the potential risks and obtain the optimal order quantity for the retailer to maximize the CVaR objective of loss aversion utility. It is shown that that the optimal order quantity for a retailer to maximize the expected loss aversion utility is smaller than expected profit maximizing (EPM) order quantity in the classical newsvendor model, which can help to explain decision bias in the newsvendor model. This study shows that the optimal order quantity with the CVaR objective can decrease in retail price under certain conditions, which has never occurred in the newsvendor literature. With the optimal order quantity under the CVaR objective, it is proved that the retailer’s expected loss aversion utility is decreasing in the confidence level. This confirms the fact that high return means high risk, while low risk comes with low return. Based on the results, several management insights are suggested for the loss-averse newsvendor model.

Description: As an extension of the fuzzy set, the hesitant fuzzy set is used to effectively solve the hesitation of decision-makers in group decision-making and to rigorously express the decision information. In this paper, we first introduce some new hesitant fuzzy Hamacher power-aggregation operators for hesitant fuzzy information based on Hamacher t-norm and t-conorm. Some desirable properties of these operators is shown, and the interrelationships between them are given. Furthermore, the relationships between the proposed aggregation operators and the existing hesitant fuzzy power-aggregation operators are discussed. Based on the proposed aggregation operators, we develop a new approach for multiple-attribute decision-making problems. Finally, a practical example is provided to illustrate the effectiveness of the developed approach, and the advantages of our approach are analyzed by comparison with other existing approaches.

Description: In this work, we consider the general class of difference equations (covered many equations that have been studied by other authors or that have never been studied before), as a means of establishing general theorems, for the asymptotic behavior of its solutions. Namely, we state new necessary and sufficient conditions for local asymptotic stability of these equations. In addition, we study the periodic solution with period two and three. Our results essentially extend and improve the earlier ones.

Description: This study considers an asset-liability optimization model based on constraint robustness with the chance constraint of capital to risk assets ratio in a safety-first framework under the condition that only moment information is known. This paper aims to extend the proposed single-objective capital to risk assets ratio chance constrained optimization model in the literature by considering the multi-objective constraint robustness approach in a modified safety-first framework. To solve the optimization model, we develop a deterministic convex counterpart of the capital to risk assets ratio robust probability constraint. In a consolidated risk measure of variance and safety-first framework, the proposed distributionally-robust capital to risk asset ratio chance-constrained optimization model guarantees banks will meet the capital requirements of Basel III with a likelihood of 95% irrespective of changes in the future market value of assets. Even under the worst-case scenario, i.e., when loans default, our proposed capital to risk asset ratio chance-constrained optimization model meets the minimum total requirements of Basel III. The practical implications of the findings of this study are that the model, when applied, will provide safety against extreme losses while maximizing returns and minimizing risk, which is prudent in this post-financial crisis regime.

Description: In this paper, a mathematical model based on the one-parameter Mittag-Leffler function is proposed to be used for the first time to describe the relation between the unemployment rate and the inflation rate, also known as the Phillips curve. The Phillips curve is in the literature often represented by an exponential-like shape. On the other hand, Phillips in his fundamental paper used a power function in the model definition. Considering that the ordinary as well as generalised Mittag-Leffler function behave between a purely exponential function and a power function it is natural to implement it in the definition of the model used to describe the relation between the data representing the Phillips curve. For the modelling purposes the data of two different European economies, France and Switzerland, were used and an “out-of-sample” forecast was done to compare the performance of the Mittag-Leffler model to the performance of the power-type and exponential-type model. The results demonstrate that the ability of the Mittag-Leffler function to fit data that manifest signs of stretched exponentials, oscillations or even damped oscillations can be of use when describing economic relations and phenomenons, such as the Phillips curve.

Description: By using the Kolmogorov-Arnold-Moser (KAM) theory, we investigate the stability of two elliptic equilibrium points (zero equilibrium and negative equilibrium) of the difference equation t n + 1 = α t n + β t n 2 − t n − 1 , n = 0 , 1 , 2 , … , where are t − 1 , t 0 , α ∈ R , α ≠ 0 , β 〉 0 . By using the symmetries we find the periodic solutions with some periods. Finally, some numerical examples are given to verify our theoretical results.

Description: 〈p〉Publication date: Available online 29 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Claudio Arbib, Mustafa Ç. Pınar, Matteo Tonelli〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Consider a three-level non-capacitated location/pricing problem: a firm first decides which facilities to open, out of a finite set of candidate sites, and sets service prices with the aim of revenue maximization; then a second firm makes the same decisions after checking competing offers; finally, customers make individual decisions trying to minimize costs that include both purchase and transportation. A restricted two-level problem can be defined to model an optimal reaction of the second firm to known decision of the first.〈/p〉 〈p〉For non-metric costs, the two-level problem corresponds to 〈span〉Envy-free Pricing〈/span〉 or to a special 〈span〉Network Pricing〈/span〉 problem, and is 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si65.svg"〉〈mi mathvariant="bold-script"〉APX〈/mi〉〈/math〉-complete even if facilities can be opened at no fixed cost. Our focus is on the metric 1-dimensional case, a model where customers are distributed on a main communication road and transportation cost is proportional to distance. We describe polynomial-time algorithms that solve two- and three-level problems with opening costs and single 1〈sup〉〈em〉st〈/em〉〈/sup〉 level facility. Quite surprisingly, however, even the two-level problem with no opening costs becomes 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si66.svg"〉〈mi mathvariant="bold-script"〉NP〈/mi〉〈/math〉-hard when two 1〈sup〉〈em〉st〈/em〉〈/sup〉 level facilities are considered.〈/p〉 〈/div〉

Description: 〈p〉Publication date: Available online 29 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Zachary Feinstein〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We construct a continuous time model for price-mediated contagion precipitated by a common exogenous stress to the banking book of all firms in the financial system. In this setting, firms are constrained so as to satisfy a risk-weight based capital ratio requirement. We use this model to find analytical bounds on the risk-weights for assets as a function of the market liquidity. Under these appropriate risk-weights, we find existence and uniqueness for the joint system of firm behavior and the asset prices. We further consider an analytical bound on the firm liquidations, which allows us to construct exact formulas for stress testing the financial system with deterministic or random stresses. Numerical case studies are provided to demonstrate various implications of this model and analytical bounds.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 29 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Bo Jin〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In a recent paper, Galle, Barnhart, and Jaillet [Galle, V., Barnhart, C., & Jaillet, P. (2018). A new binary formulation of the restricted container relocation problem based on a binary encoding of configurations. 〈em〉European Journal of Operational Research, 267〈/em〉(2), 467–477] introduced a new variant of the container relocation problem (CRP), named the relaxed restricted CRP, where every container can be relocated at most once for retrieving each target container. The authors also proposed a binary integer programming model for formulating the relaxed restricted CRP. In this paper, it is first shown that the proposed model contains two deficiencies in formulating the “last in, first out” (LIFO) policy. These deficiencies will cause the solutions obtained by the model to correspond to infeasible configurations or infeasible relocation sequences. Then, the LIFO policy is analyzed in detail and reformulated as linear constraints correctly. Lastly, the corrected integer programming formulation is presented. Computational experiments show that the corrected model dramatically reduces complexity and improves performance.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 28 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Mike G. Tsionas〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Mitropoulos et al. (Mitropoulos P., M. A. Talias, and I. Mitropoulos, 2015, Combining stochastic DEA with Bayesian analysis to obtain statistical properties of the efficiency scores: An application to Greek public hospitals. European Journal of Operational Research 243, 302-311) suggested the use of a Bayesian approach in Data Envelopment Analysis (DEA) which can be used to obtain posterior distributions of efficiency scores. In this paper, we avoid their assumption that alternative data sets are simulated from the predictive distribution obtained from their simple data generating process of a normal distribution for the data. The new approach has two significant advantages. First, the posterior proposed in this paper is coherent or principled in the sense that it is consistent with the DEA formulation. Second, and perhaps surprisingly, it is not necessary to solve linear programming problems for each observation in the sample. Bayesian inference is organized around Markov Chain Monte Carlo techniques that can be implemented quite easily. We conduct extensive Monte Carlo experiments to investigate the finite-sample properties of the new approach. We also provide an application to a large U.S banking data set. The sample is an unbalanced panel of US banks with 2,397 bank–year observations for 285 banks. The main purpose of the analysis is to compare distributions of efficiency scores. Relative to DEA, Bayes DEA provides different efficiency scores and their sample distribution has significantly less probability concentration around unity. The comparison with bootstrap-DEA shows that results from Bayes DEA are in broad agreement.〈/p〉〈/div〉

Description: The mean-shift method is a convenient mode-seeking method. Using a principle of the sample mean over an analysis window, or kernel, in a data space where samples are distributed with bias toward the densest direction of sample from the kernel center, the mean-shift method is an attempt to seek the densest point of samples, or the sample mode, iteratively. A smaller kernel leads to convergence to a local mode that appears because of statistical fluctuation. A larger kernel leads to estimation of a biased mode affected by other clusters, abnormal values, or outliers if they exist other than in the major cluster. Therefore, optimal selection of the kernel size, which is designated as the bandwidth in many reports of the literature, represents an important problem. As described herein, assuming that the major cluster follows a Gaussian probability density distribution, and, assuming that the outliers do not affect the sample mode of the major cluster, and, by adopting a Gaussian kernel, we propose a new mean-shift by which both the mean vector and covariance matrix of the major cluster are estimated in each iteration. Subsequently, the kernel size and shape are updated adaptively. Numerical experiments indicate that the mean vector, covariance matrix, and the number of samples of the major cluster can be estimated stably. Because the kernel shape can be adjusted not only to an isotropic shape but also to an anisotropic shape according to the sample distribution, the proposed method has higher estimation precision than the general mean-shift.

Description: 〈p〉Publication date: Available online 21 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Zelin Zhang, Minghui Ma, Peter T.L. Popkowski Leszczyc, Hejun Zhuang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉This research proposes an analytical model of the joint optimization of coupon face value and duration together with the product price, and determines the impact of coupon design on consumers’ redemption behavior. A model of rational forward-looking consumers’ redemption behavior is derived that incorporates forgetting (to redeem) and stochastic redemption costs.〈/p〉 〈p〉Results show that when product price is exogenous, long-duration coupons may result in increased seller profits and always increase consumer surplus. Moreover, a one-period coupon is never optimal when (1) the difference in valuations for high-value (loyal) and low-value (non-loyal) consumers or (2) the coupon face value is larger than the redemption costs of high-value consumers. Long-duration coupons tend to be optimal when the level of recall of high-value consumers is sufficiently low, which reduces redemption by high-value consumers.〈/p〉 〈p〉Coupon duration together with face value plays an important role in coupons’ ability to price discriminate between different consumer segments and to avoid head-on competition with other sellers. Results can replicate empirically observed redemptions patterns, which has important implications for the strategic targeting of coupons to different consumer segments.〈/p〉 〈p〉A coupon may result in an increase or decrease in price. When the difference in valuation between high-value and low-value consumers is high (relative to the redemption costs), a seller can either reduce price and lower face value or increase coupon duration for the purpose of avoiding redemption by high-value consumers.〈/p〉 〈/div〉

Description: In this paper, we establish generalized Suzuki-simulation-type contractive mapping and prove fixed point theorems on non-Archimedean quasi modular metric spaces. As an application, we acquire graphic-type results.

Description: In this study we introduce several new Ostrowski-type inequalities for both left and right sided fractional integrals of a function g with respect to another function ψ . Our results generalized the ones presented previously by Farid. Furthermore, two illustrative examples are presented to support our results.

Description: 〈p〉Publication date: Available online 21 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Sturla F. Kvamsdal, José M. Maroto, Manuel Morán, Leif K. Sandal〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Seasonality or periodicity–biological, environmental, or economic–are fundamental properties of most marine fisheries. We propose a generic infinite horizon discrete time fisheries management model by modifying existing models and frameworks of analysis to reflect seasonal variation or more general multiperiodicity in parameters, variables, or functional forms. Our model captures such variations via repeated cycles of multiple intervals with differing characteristics. The framework offers a simple and intuitive set up of arbitrary periodicity and seasonality in any feature, which significantly increases model realism. Further, it distances itself from continuous time modeling approaches where uniqueness and solvability of periodic models generally are difficult to assert. In our setting, the governing equations for the time-dependent value function of the management optimization problem are shown to be equivalent to a high-dimensional contraction and hence ensure uniqueness and a feasible solution algorithm. We illustrate our approach using a simple example to demonstrate that accounting for seasonality in fisheries management can improve outcomes considerably. Our framework also provides for analysis of seasonal regulatory measures. Ultimately, our approach applies to renewable resource management more generally and to many infinite-horizon, discrete time optimization problems with periodic features.〈/p〉〈/div〉

Description: Brazil is an important player when it comes to biofuel and agricultural production. The knowledge of the price relationship between these markets has increasing importance. This paper adopts several tools, namely the Bai–Perron test of breakpoints, the Johansen cointegration test and the vector error correction model exploited by the orthogonal impulse response and the forecast error variance decomposition, for investigating the price transmission among the ethanol and the main Brazil’s agricultural commodities (sugar, cotton, arabica coffee, robusta coffee, live cattle, corn and soybean). The data series cover the period from January 2011 up to December 2018. The results suggest a stronger price transmission from the ethanol commodity to the agricultural commodities, rather than the opposite situation.

Description: We formulate a new class of fractional difference and sum operators, study their fundamental properties, and find their discrete Laplace transforms. The method depends on iterating the fractional sum operators corresponding to fractional differences with discrete Mittag–Leffler kernels. The iteration process depends on the binomial theorem. We note in particular the fact that the iterated fractional sums have a certain semigroup property, and hence, the new introduced iterated fractional difference-sum operators have this semigroup property as well.

Description: In this article, we make a detailed study of some mathematical aspects associated with a generalized Lévy process using fractional diffusion equation with Mittag–Leffler kernel in the context of Atangana–Baleanu operator. The Lévy process has several applications in science, with a particular emphasis on statistical physics and biological systems. Using the continuous time random walk, we constructed a fractional diffusion equation that includes two fractional operators, the Riesz operator to Laplacian term and the Atangana–Baleanu in time derivative, i.e., a A B D t α ρ ( x , t ) = K α , μ ∂ x μ ρ ( x , t ) . We present the exact solution to model and discuss how the Mittag–Leffler kernel brings a new point of view to Lévy process. Moreover, we discuss a series of scenarios where the present model can be useful in the description of real systems.

Description: This research paper proposes a derivative-free method for solving systems of nonlinear equations with closed and convex constraints, where the functions under consideration are continuous and monotone. Given an initial iterate, the process first generates a specific direction and then employs a line search strategy along the direction to calculate a new iterate. If the new iterate solves the problem, the process will stop. Otherwise, the projection of the new iterate onto the closed convex set (constraint set) determines the next iterate. In addition, the direction satisfies the sufficient descent condition and the global convergence of the method is established under suitable assumptions. Finally, some numerical experiments were presented to show the performance of the proposed method in solving nonlinear equations and its application in image recovery problems.

Description: 〈p〉Publication date: Available online 20 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Chandra Ade Irawan, Majid Eskandarpour, Djamila Ouelhadj, Dylan Jones〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Scheduling maintenance routing for an offshore wind farm is a challenging and complex task. The problem is to find the best routes for the Crew Transfer Vessels to maintain the turbines in order to minimise the total cost. This paper primarily proposes an efficient solution method to solve the deterministic maintenance routing problem in an offshore wind farm. The proposed solution method is based on the Large Neighbourhood Search metaheuristic. The efficiency of the proposed metaheuristic is validated against state of the art algorithms. The results obtained from the computational experiments validate the effectiveness of the proposed method. In addition, as the maintenance activities are affected by uncertain conditions, a simulation-based optimisation algorithm is developed to tackle these uncertainties. This algorithm benefits from the fast computational time and solution quality of the proposed metaheuristic, combined with Monte Carlo simulation. The uncertain factors considered include the travel time for a vessel to visit turbines, the required time to maintain a turbine, and the transfer time for technicians and equipment to a turbine. Moreover, the proposed simulation-based optimisation algorithm is devised to tackle unpredictable broken-down turbines. The performance of this algorithm is evaluated using a case study based on a reference wind farm scenario developed in the EU FP7 LEANWIND project.〈/p〉〈/div〉

Description: The operation of many real-world systems, e.g., servers of data centers, is accompanied by the heating of a server. Correspondingly, certain cooling mechanisms are used. If the server becomes overheated, it interrupts processing of customers and needs to be cooled. A customer is lost when its service is interrupted. To prevent overheating and reduce the customer loss probability, we suggest temporal termination of service of new customers when the temperature of the server reaches the predefined threshold value. Service is resumed after the temperature drops below another threshold value. The problem of optimal choice of the thresholds (with respect to the chosen economical criterion) is numerically solved under quite general assumptions about the parameters of the system (Markovian arrival process, phase-type distribution of service time, and accounting for customers impatience). Numerical examples are presented.

Description: 〈p〉Publication date: Available online 20 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Simon J. Höller, Raik Özsen, Ulrich W. Thonemann〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Order expediting is an inventory control practice that allows companies to reduce inventory while maintaining service levels. However, expediting outstanding orders is costly and a trade-off must be made between expediting orders and holding inventory. We model the problem as a periodic-review inventory system with the option to move outstanding units forward in the replenishment pipeline. The objective is to minimize the sum of expected inventory holding and expediting costs per period subject to a minimum expected service level constraint. We consider a generalized base-stock policy where outstanding units are expedited when the inventory level drops below a certain threshold. We develop structural properties and present an efficient procedure to determine the optimal policy parameters. In a numerical study with real-world data, we show that our expediting policy offers substantial savings compared to other policies. We also provide managerial insights by numerically analyzing how the model parameters impact the savings.〈/p〉〈/div〉

Description: In this paper, we introduce the concept of a n 0 -order weighted pseudo Δ n 0 δ -almost automorphic function under the matched space for time scales and we present some properties. The results are valid for q-difference dynamic equations among others. Moreover, we obtain some sufficient conditions for the existence of weighted pseudo Δ n 0 δ -almost automorphic mild solutions to a class of semilinear dynamic equations under the matched space. Finally, we end the paper with a further discussion and some open problems of this topic.

Description: In this paper, based on the very recent work by Nandal et al. (Nandal, A.; Chugh, R.; Postolache, M. Iteration process for fixed point problems and zeros of maximal monotone operators. Symmetry 2019, 11, 655.), we propose a new generalized viscosity implicit rule for finding a common element of the fixed point sets of a finite family of nonexpansive mappings and the sets of zeros of maximal monotone operators. Utilizing the main result, we first propose and investigate a new general system of generalized equilibrium problems, which includes several equilibrium and variational inequality problems as special cases, and then we derive an implicit iterative method to solve constrained multiple-set split convex feasibility problem. We further combine forward-backward splitting method and generalized viscosity implicit rule for solving monotone inclusion problem. Moreover, we apply the main result to solve convex minimization problem.

Description: 〈p〉Publication date: Available online 20 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): M. Fampa, D. Lubke, F. Wang, H. Wolkowicz〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We consider a parametric convex quadratic programming (CQP) relaxation for the quadratic knapsack problem (QKP). This relaxation maintains partial quadratic information from the original QKP by perturbing the objective function to obtain a concave quadratic term. The nonconcave part generated by the perturbation is then linearized by a standard approach that lifts the problem to matrix space. We present a primal-dual interior point method to optimize the perturbation of the quadratic function, in a search for the tightest upper bound for the QKP. We prove that the same perturbation approach, when applied in the context of semidefinite programming (SDP) relaxations of the QKP, cannot improve the upper bound given by the corresponding linear SDP relaxation. The result also applies to more general integer quadratic problems. Finally, we propose new valid inequalities on the lifted matrix variable, derived from cover and knapsack inequalities for the QKP, and present separation problems to generate cuts for the current solution of the CQP relaxation. Our best bounds are obtained alternating between optimizing the parametric quadratic relaxation over the perturbation and applying cutting planes generated by the valid inequalities proposed.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 20 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Yusuke Zennyo〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper examines strategic contracting between a monopoly platform and suppliers that sell their goods through the platform. I consider two competing suppliers: a high-volume supplier with the larger potential demand and a low-volume supplier with the smaller one. Each supplier chooses one of two contracts: wholesale or agency. The platform has to strategically determine the royalty rate for the agency contract by taking into account which contracts the suppliers will choose. I show that the platform offers a low (high) royalty rate to induce the suppliers to adopt the agency (wholesale) contract when product substitutability is low (high) enough. More interestingly, when the degree of substitution is at an intermediate level, asymmetric contracting, in which only the low-volume supplier adopts the agency contract, can arise in equilibrium. This result is related to the fact that many long-tail and niche products with lower potential market sizes are traded on platform-based marketplaces, such as Amazon Marketplace and Walmart Marketplace.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 31 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Shu Guo, Tsan-Ming Choi, Bin Shen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Motivated by the observed industrial issues, we analytically develop a fashion supply chain consisting of one manufacturer and two competing retailers and investigate how retail competition and consumer returns affect green product development in fashion apparel. In the basic model, that is, the pure “product greenness level” game, we find that the optimal greenness level of the fashion product decreases along with the level of market competition. This finding implies that a more competitive market leads to a lower optimal greenness level. We also identify that when the consumer return rate increases, the optimal product greenness level is substantially reduced. In the extended model with joint decisions on greenness and pricing, we find that the optimal product greenness level for the whole channel is always higher in the scenario when both retailers charge a higher retail price than in the case with a lower retail price. As such, the underdevelopment of green fashion products is a result of fashion industry features, such as an extremely competitive environment for green product development, relatively low retail prices for fashion products, and high consumer return rates. Therefore, fashion companies should join a co-opetition game for the green product market and simultaneously enhance their efficiency in managing consumer returns. To support our analytical findings, we conduct extensive industrial interviews with various representative companies. Based on this multi-methodological approach (MMA), this paper generates practice-relevant managerial insights that not only contribute to the literature, but also act as valuable references for industrialists.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 31 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Daqiang Chen, Joshua Ignatius, Danzhi Sun, Mark Goh, Shalei Zhan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper addresses the problem of the firms operating on cross-border or inter-regional platforms that are subject to the enforcement of each local government's carbon emissions regulatory policy, thus causing an imbalance in the sharing of the burden of the greening of the total supply chain. We introduce the concept of equity as the incentive mechanism to coordinate this green supply chain which is a function of the carbon emission permits and the revenue generated by the firms. Due to the complexity and imbalance in the original incentive mechanism to this problem, we provide a new equivalent supply chain network equilibrium model under elastic demand based on user equilibrium theory. We state the user equilibrium conditions and provide the equivalent formulation. We show the trade-offs under various carbon emissions regulatory policies. A product with higher price elasticity and carbon emission intensity not only hampers the firm from gaining a higher revenue, but it also reduces the equity of the system under an invariant emission regulatory policy.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 28 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Noemie Balouka, Izack Cohen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper suggests a robust optimization approach for the multi-mode resource-constrained project scheduling problem with uncertain activity durations. The objective is to minimize the worst-case project duration by deciding on activity modes, resource allocations and a schedule baseline. The problem is solved by a Benders decomposition approach with specialized cuts. We consider polyhedral uncertainty sets in which the level of conservatism can be adjusted. Using a computational study in which various problem instances are explored under varying levels of uncertainty, conservatism and several types of duration distributions, we provide insights about the price of robustness and the performance of the approach. The hope is that these insights can guide future multi-mode project scheduling implementations when there is partial information about the distribution of activity durations.〈/p〉〈/div〉

Description: The automatic identification of rock type in the field would aid geological surveying, education, and automatic mapping. Deep learning is receiving significant research attention for pattern recognition and machine learning. Its application here has effectively identified rock types from images captured in the field. This paper proposes an accurate approach for identifying rock types in the field based on image analysis using deep convolutional neural networks. The proposed approach can identify six common rock types with an overall classification accuracy of 97.96%, thus outperforming other established deep-learning models and a linear model. The results show that the proposed approach based on deep learning represents an improvement in intelligent rock-type identification and solves several difficulties facing the automated identification of rock types in the field.

Description: In this paper, we establish a new q-integral identity, the result is then used to derive two q-integral inequalities of Simpson-type involving strongly preinvex functions. Some special cases of the obtained results are also considered, it is shown that several new and previously known results can be derived via generalized strongly preinvex functions and quantum integrals.

Description: The aim of this paper is to introduce a modified viscosity iterative method to approximate a solution of the split variational inclusion problem and fixed point problem for a uniformly continuous multivalued total asymptotically strictly pseudocontractive mapping in C A T ( 0 ) spaces. A strong convergence theorem for the above problem is established and several important known results are deduced as corollaries to it. Furthermore, we solve a split Hammerstein integral inclusion problem and fixed point problem as an application to validate our result. It seems that our main result in the split variational inclusion problem is new in the setting of C A T ( 0 ) spaces.

Description: We give some polynomial sequence relations that are generalizations of the Sury-type identities. We provide two proofs, one based on an elementary identity and the other using the method of generating functions.

Description: 〈p〉Publication date: Available online 13 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Gilberto Montibeller, Pratik Patel, Victor J. del Rio Vilas〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Multi-criteria assessments are increasingly being employed in the prioritisation of health threats, supporting decision processes related to health risk management. The use of multi-criteria analysis in this context is welcome, as it facilitates the consideration of multiple impacts of health threats, it can encompass the use of expert judgment to complement and amalgamate the evidence available, and it permits the modelling of policy makers’ priorities. However, these assessments often lack a clear multi-criteria conceptual framework, in terms of both axiomatic rigour and adequate procedures for preference modelling. Such assessments are 〈em〉ad hoc〈/em〉 from a multi-criteria decision analysis perspective, despite the strong health expertise used in constructing these models. In this paper we critically examine some key assumptions and modelling choices made in these assessments, comparing them with the best practices of multi-attribute value analysis. Furthermore, we suggest a set of guidelines on how simulation studies might be employed to assess the impact of these modelling choices. We apply these guidelines to two relevant studies available in the health threat prioritisation domain. We identify severe variability in our simulations due to poor modelling choices, which could cause changes in the ranking of threats being assessed and thus lead to alternative policy recommendations than those suggested in their reports. Our results confirm the importance of carefully designing multi-criteria evaluation models for the prioritisation of health threats.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 13 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Antoine Lesage-Landry, Joshua A. Taylor〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We construct a model for transmission planning with both alternating and direct current lines, the latter of which can be interfaced via either line-commutated converters or voltage-source converters. The transmission expansion problem is nonlinear and nonconvex. Thus, nonlinear solvers cannot guarantee their convergence to the global optimum of the problem. We use relaxations and approximations to formulate a mixed-integer second-order cone transmission expansion model, which can be solved to optimality by current industrial solvers. We base our formulation on the branch flow relaxation. We include losses and reactive power placement, and consider direct current lines connected by both line-commutated converters and voltage-sourced converters. We show that our approach lowers the expansion cost on 6-bus and 24-bus system examples. We evaluate the feasibility of our formulation using a semidefinite relaxation of optimal power flow and find that the resulting plan admits feasible or close to feasible power flows.〈/p〉〈/div〉

Description: The Van der Pol oscillator is investigated by the parameter control method. This method only needs to control one parameter of the Van der Pol oscillator by a simple periodic function; then, the Van der Pol oscillator can behave chaotically from the stable limit cycle. Based on the new Van der Pol oscillator with variable parameter (VdPVP), some dynamical characteristics are discussed by numerical simulations, such as the Lyapunov exponents and bifurcation diagrams. The numerical results show that there exists a positive Lyapunov exponent in the VdPVP. Therefore, an encryption algorithm is designed by the pseudo-random sequences generated from the VdPVP. This simple algorithm consists of chaos scrambling and chaos XOR (exclusive-or) operation, and the statistical analyses show that it has good security and encryption effectiveness. Finally, the feasibility and validity are verified by simulation experiments of image encryption.

Description: 〈p〉Publication date: Available online 12 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Valentin Zelenyuk〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The main goal of this paper is to explore the possible solutions to a ‘big data’ problem related to the very large dimensions of input–output data. In particular, we focus on the cases of severe ‘curse of dimensionality’ problem that require dimension-reduction prior to using Data Envelopment Analysis. To achieve this goal, we have presented some theoretical grounds and performed a new to the literature simulation study where we explored the price-based aggregation as a solution to address the problem of very large dimensions.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 12 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): M. Densing〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A stored commodity is sold under a capacity constraint depending on an exogenous random market price, and, alternatively, a service contract can be provided in which the selling amount must be held constant over time independent of price changes. The seller of the commodity is assumed to optimize the trade-off between the received payment for the provision of the service and the loss of flexibility by the reduced selling on the market. The chosen setup allows for closed-form solutions, such that the analysis is of theoretical interest. A potential application is hydropower storage optimization against exogenous electricity prices with the option to enter contracts for providing spinning reserve; spinning reserve is needed to stabilize large-scale power systems. A single-period model is considered, and the storage level of the commodity is bounded from below in expectation. These simplifications allow a closed-form solution of bang-bang type, even under our assumption of an infinite probability space.〈/p〉〈/div〉

Description: Radial basis function-based quasi-interpolation performs efficiently in high-dimensional approximation and its applications, which can attain the approximant and its derivatives directly without solving any large-scale linear system. In this paper, the bivariate multi-quadrics (MQ) quasi-interpolation is used to simulate two-dimensional (2-D) Burgers’ equation. Specifically, the spatial derivatives are approximated by using the quasi-interpolation, and the time derivatives are approximated by forward finite difference method. One advantage of the proposed scheme is its simplicity and easy implementation. More importantly, the proposed scheme opens the gate to meshless adaptive moving knots methods for the high-dimensional partial differential equations (PDEs) with shock or soliton waves. The scheme is also applicable to other non-linear high-dimensional PDEs. Two numerical examples of Burgers’ equation (shock wave equation) and one example of the Sine–Gordon equation (soliton wave equation) are presented to verify the high accuracy and efficiency of this method.

Description: Context-aware video recommender systems (CAVRS) seek to improve recommendation performance by incorporating contextual features along with the conventional user-item ratings used by video recommender systems. In addition, the selection of influential and relevant contexts has a significant effect on the performance of CAVRS. However, it is not guaranteed that, under the same contextual scenario, all the items are evaluated by users for providing dense contextual ratings. This problem cause contextual sparsity in CAVRS because the influence of each contextual factor in traditional CAVRS assumes the weights of contexts homogeneously for each of the recommendations. Hence, the selection of influencing contexts with minimal conflicts is identified as a potential research challenge. This study aims at resolving the contextual sparsity problem to leverage user interactions at varying contexts with an item in CAVRS. This problem may be investigated by considering a formal approximation of contextual attributes. For the purpose of improving the accuracy of recommendation process, we have proposed a novel contextual information selection process using Soft-Rough Sets. The proposed model will select a minimal set of influencing contexts using a weights assign process by Soft-Rough sets. Moreover, the proposed algorithm has been extensively evaluated using “LDOS-CoMoDa” dataset, and the outcome signifies the accuracy of our approach in handling contextual sparsity by exploiting relevant contextual factors. The proposed model outperforms existing solutions by identifying relevant contexts efficiently based on certainty, strength, and relevancy for effective recommendations.

Description: If a differentiable function f : [ a , b ] → R and a point η ∈ [ a , b ] satisfy f ( η ) − f ( a ) = f ′ ( η ) ( η − a ) , then the point η is called a Flett’s mean value point of f in [ a , b ] . The concept of Flett’s mean value points can be generalized to the 2-dimensional Flett’s mean value points as follows: For the different points r ^ and s ^ of R × R , let L be the line segment joining r ^ and s ^ . If a partially differentiable function f : R × R → R and an intermediate point ω ^ ∈ L satisfy f ( ω ^ ) − f ( r ^ ) = ω ^ − r ^ , f ′ ( ω ^ ) , then the point ω ^ is called a 2-dimensional Flett’s mean value point of f in L. In this paper, we will prove the Hyers–Ulam stability of 2-dimensional Flett’s mean value points.

Description: The goal of this research is to extend and investigate an improved approach for calculating the weighted Moore–Penrose (WMP) inverses of singular or rectangular matrices. The scheme is constructed based on a hyperpower method of order ten. It is shown that the improved scheme converges with this rate using only six matrix products per cycle. Several tests are conducted to reveal the applicability and efficiency of the discussed method, in contrast with its well-known competitors.

Description: We consider a differential game of fisheries in a fan-like control structure of the type “supervisor—several agents”. The dynamics of the controlled system is described by a non-linear differential equation model which is identified on the Azov Sea data. An averaging by two spatial coordinates is conducted. Different information structures of the game are generated by the control methods of compulsion (supervisor restricts the feasible strategies of agents) and impulsion (she exerts an impact to their payoff functionals). Both Stackerlberg and inverse Stackelberg games are considered. For the numerical investigation we use a discretization of the initial model and the method of qualitatively representative scenarios in simulation modeling.

Description: 〈p〉Publication date: Available online 8 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Landir Saviniec, Maristela O. Santos, Alysson M. Costa, Lana M.R. dos Santos〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉High school timetabling problems consist in building periodic timetables for class-teacher meetings considering compulsory and non-compulsory requirements. This family of problems has been widely studied since the 1950s, mostly via mixed-integer programming and metaheuristic techniques. However, the efficient search of optimal or near-optimal solutions is still a challenge for many problems of practical size. In this paper, we investigate mixed-integer programming formulations and a parallel metaheuristic based algorithm for solving high school timetabling problems with compactness and balancing requirements. We propose two pattern-based formulations and a solution algorithm that simultaneously exploits column generation and a team of metaheuristics to build and improve solutions. Extensive computational experiments conducted with real-world instances demonstrate that our formulations are competitive with the best existing high school timetabling formulations, while our parallel algorithm presents superior performance to alternative methods available in the literature.〈/p〉〈/div〉

Description: This paper proposes a model of the dynamics of credit contagion through non-performing loans on financial networks. Credit risk contagion is modeled in the context of the classical SIS (Susceptibles-Infected-Susceptibles) epidemic processes on networks but with a fundamental novelty. In fact, we assume the presence of two different classes of infected agents, and then we differentiate the dynamics of assets subject to idiosyncratic risk from those affected by systemic risk by adopting a SIIS (Susceptible-Infected1-Infected2-Susceptible) model. In the recent literature in this field, the effect of systemic credit risk on the performance of the financial network is a hot topic. We perform numerical simulations intended to explore the roles played by two different network structures on the long-term behavior of assets affected by systemic risk in order to analyze the effect of the topology of the underlying network structure on the spreading of systemic risk on the structure. Random graphs, i.e., the Erdös–Rényi model, are considered “benchmark” network structures while core-periphery structures are often indicated in the literature as idealized structures, although they are able to capture interesting, specific features of real-world financial networks. Moreover, as a matter of comparison, we also perform numerical experiments on small-world networks.

Description: 〈p〉Publication date: Available online 5 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Kai A. Konrad〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies the attack-and-defence game between a web user and a whole set of players over this user’s ‘valuable secrets.’ The number and type of these valuable secrets are the user’s private information. Attempts to tap information as well as privacy protection are costly. The multiplicity of secrets is of strategic value for the holders of these secrets. Users with few secrets keep their secrets private with some probability, even though they do not protect them. Users with many secrets protect their secrets at a cost that is smaller than the value of the secrets protected. The analysis also accounts for multiple redundant information channels with cost asymmetries, relating the analysis to attack-and-defence games with a weakest link.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 2 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): C. Archetti, D. Feillet, A. Mor, M.G. Speranza〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The dynamic traveling salesman problem with stochastic release dates (DTSP-srd) is a problem in which a supplier has to deliver parcels to its customers. These parcels are delivered to its depot while the distribution is taking place. The arrival time of a parcel to the depot is called its release date. In the DTSP-srd, release dates are stochastic and dynamically updated as the distribution takes place. The objective of the problem is the minimization of the total time needed to serve all customers, given by the sum of the traveling time and the waiting time at the depot. The problem is represented as a Markov Decision Process and is solved through a reoptimization approach. Two models are proposed for the problem to be solved at each stage. The first model is stochastic and exploits the entire probabilistic information available for the release dates. The second model is deterministic and uses an estimation of the release dates. An instance generation procedure is proposed to simulate the evolution of the information to perform computational tests. The results show that a more frequent reoptimization provides better results across all tested instances and that the stochastic model performs better than the deterministic model. The main drawback of the stochastic model lies in the computational time required to evaluate a solution, which makes an iteration of the heuristic substantially more time-consuming than in the case where the deterministic model is used.〈/p〉〈/div〉

Description: The Firoozbakht, Nicholson, and Farhadian conjectures can be phrased in terms of increasingly powerful conjectured bounds on the prime gaps g n : = p n + 1 - p n . While a general proof of any of these conjectures is far out of reach, I shall show that all three of these conjectures are unconditionally and explicitly verified for all primes below the as yet unknown location of the 81st maximal prime gap, certainly for all primes p 〈 2 64 . For the Firoozbakht conjecture itself this is a rather minor improvement on currently known results, but for the somewhat stronger Nicholson and Farhadian conjectures this may be considerably more interesting. Sequences: A005250 A002386 A005669 A000101 A107578 A246777 A246776.

Description: In the present paper, we study geodesic mappings of special pseudo-Riemannian manifolds called V n ( K ) -spaces. We prove that the set of solutions of the system of equations of geodesic mappings on V n ( K ) -spaces forms a special Jordan algebra and the set of solutions generated by concircular fields is an ideal of this algebra. We show that pseudo-Riemannian manifolds admitting a concircular field of the basic type form the class of manifolds closed with respect to the geodesic mappings.

Description: In this article, we propose a modified self-adaptive conjugate gradient algorithm for handling nonlinear monotone equations with the constraints being convex. Under some nice conditions, the global convergence of the method was established. Numerical examples reported show that the method is promising and efficient for solving monotone nonlinear equations. In addition, we applied the proposed algorithm to solve sparse signal reconstruction problems.

Description: In this manuscript, we propose a solution for Volterra type fractional integral equations by using a hybrid type contraction that unifies both nonlinear and linear type inequalities in the context of metric spaces. Besides this main goal, we also aim to combine and merge several existing fixed point theorems that were formulated by linear and nonlinear contractions.

Description: The present paper investigates the numerical solution of an imprecisely defined nonlinear coupled time-fractional dynamical model of marriage (FDMM). Uncertainties are assumed to exist in the dynamical system parameters, as well as in the initial conditions that are formulated by triangular normalized fuzzy sets. The corresponding fractional dynamical system has first been converted to an interval-based fuzzy nonlinear coupled system with the help of a single-parametric gamma-cut form. Further, the double-parametric form (DPF) of fuzzy numbers has been used to handle the uncertainty. The fractional reduced differential transform method (FRDTM) has been applied to this transformed DPF system for obtaining the approximate solution of the FDMM. Validation of this method was ensured by comparing it with other methods taking the gamma-cut as being equal to one.

Description: In studying the Riccati transformation technique, some mathematical inequalities and comparison results, we establish new oscillation criteria for a non-linear fractional difference equation with damping term. Preliminary details including notations, definitions and essential lemmas on discrete fractional calculus are furnished before proceeding to the main results. The consistency of the proposed results is demonstrated by presenting some numerical examples. We end the paper with a concluding remark.

Description: The aim of this paper was to propose a systematic study of a ( 1 + 1 ) -dimensional higher order nonlinear Schrödinger equation, arising in two different contexts regarding the biological science and the nonlinear optics. We performed a Lie symmetry analysis and here present exact solutions of the equation.

Description: 〈p〉Publication date: Available online 28 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): María Isabel Hartillo-Hermoso, Haydee Jiménez-Tafur, José María Ucha-Enríquez〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A new exact algorithm for bi-objective linear integer problems is presented, based on the classic ϵ-constraint method and algebraic test sets for single-objective linear integer problems. Our method provides the complete Pareto frontier 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si19.svg"〉〈mi mathvariant="bold-script"〉N〈/mi〉〈/math〉 of non-dominated points and, for this purpose, it considers exactly 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si5.svg"〉〈mrow〉〈mo〉|〈/mo〉〈mi mathvariant="bold-script"〉N〈/mi〉〈mo〉|〈/mo〉〈/mrow〉〈/math〉 single-objective problems by using reduction with test sets instead of solving with an optimizer. Although we use Gröbner bases for the computation of test sets, which may provoke a bottleneck in principle, the computational results are shown to be promising, especially for unbounded knapsack problems, for which any usual branch-and-cut strategy could be much more expensive. Nevertheless, this algorithm can be considered as a potentially faster alternative to IP-based methods when test sets are available.〈/p〉〈/div〉

Description: This study focuses on the stochastic differential calculus of Itô, as an effective tool for the analysis of noise in forest growth and yield modeling. Idea of modeling state (tree size) variable in terms of univariate stochastic differential equation is exposed to a multivariate stochastic differential equation. The new developed multivariate probability density function and its marginal univariate, bivariate and trivariate distributions, and conditional univariate, bivariate and trivariate probability density functions can be applied for the modeling of tree size variables and various stand attributes such as the mean diameter, height, crown base height, crown width, volume, basal area, slenderness ratio, increments, and much more. This study introduces generalized multivariate interaction information measures based on the differential entropy to capture multivariate dependencies between state variables. The present study experimentally confirms the effectiveness of using multivariate interaction information measures to reconstruct multivariate relationships of state variables using measurements obtained from a real-world data set.

Description: We have introduced the new notions of R-weakly graph preserving and R-weakly α -admissible pair of multivalued mappings which includes the class of graph preserving mappings, weak graph preserving mappings as well as α -admissible mappings of type S, α * -admissible mappings of type S and α * - orbital admissible mappings of type S respectively. Some generalized contraction and rational contraction classes are also introduced for a pair of multivalued mappings and common fixed point theorems are proved in a b-metric space endowed with a graph. We have also applied our results to obtain common fixed point theorems for R-weakly α -admissible pair of multivalued mappings in a b-metric space which are the proper extension and generalization of many known results. Proper examples are provided in support of our results. Our main results and its consequences improve, generalize and extend many known fixed point results existing in literature.

Description: 〈p〉Publication date: Available online 16 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Qichen Deng, Bruno F. Santos, Richard Curran〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper presents a practical dynamic programming based methodology to optimize the long-term maintenance check schedule for a fleet of heterogeneous aircraft. It is the first time that the long-term aircraft maintenance check schedule is optimized, integrating different check types in a single schedule solution. The proposed methodology aims at minimizing the wasted interval between checks. By achieving this goal, one is also reducing the number of checks over time, increasing aircraft availability and, therefore, reducing maintenance costs, while respecting safety regulations. The model formulation takes aircraft type, status, maintenance capacity, and other operational constraints into consideration. We also validate and demonstrate the proposed methodology using fleet maintenance data from a European airline. The outcomes show that, when compared with the current practice, the number of maintenance checks can be reduced by around 7% over a period of 4 years, while computation time is less than 15 minutes. This could result in saving worth $1.1M–$3.4M in maintenance costs for a fleet of about 40 aircraft and generating more than $9.8M of revenue due to higher aircraft availability.〈/p〉〈/div〉

Description: In this paper, new refinements and improvements of Jordan’s and Kober’s inequalities are presented. We give new polynomial bounds for the s i n c ( x ) and cos ( x ) functions based on the interpolation and approximation method. The results show that our bounds are tighter than the previous methods.

Description: 〈p〉Publication date: Available online 14 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Urtats Etxegarai, Eva Portillo, Jon Irazusta, Lucien Koefoed, Nikola Kasabov〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this work, a heuristic as operational tool to estimate the lactate threshold and to facilitate its integration into the training process of recreational runners is proposed. To do so, we formalize the principles for the lactate threshold estimation from empirical data and an iterative methodology that enables experience based learning. This strategy arises as a robust and adaptive approach to solve data analysis problems. We compare the results of the heuristic with the most commonly used protocol by making a first quantitative error analysis to show its reliability. Additionally, we provide a computational algorithm so that this quantitative analysis can be easily performed in other lactate threshold protocols. With this work, we have shown that a heuristic (%60 of 〈em〉endurance running speed reserve〈/em〉), serves for the same purpose of the most commonly used protocol in recreational runners, but improving its operational limitations of accessibility and consistent use.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 13 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): P. Goos, U. Syafitri, B. Sartono, A.R. Vazquez〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Mixture experiments usually involve various constraints on the proportions of the ingredients of the mixture under study. In this paper, inspired by the fact that the available stock of certain ingredients is often limited, we focus on a new type of constraint, which we refer to as an ingredient availability constraint. This type of constraint substantially complicates the search for optimal designs for mixture experiments. One difficulty, for instance, is that the optimal number of experimental runs is not known a priori. The resulting optimal experimental design problem belongs to the class of nonlinear nonseparable multidimensional knapsack problems. We present a variable neighborhood search algorithm as well as a mixed integer nonlinear programming approach to tackle the problem to identify D- and I-optimal designs for mixture experiments when there is a limited stock of certain ingredients, and we show that the variable neighborhood descent algorithm is highly competitive in terms of solution quality and computing time.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 14 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Truong Van Nguyen, Li Zhou, Alain Yee Loong Chong, Boying Li, Xiaodie Pu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Remanufacturing has received increasing attention from researchers over the last decade. While many associated operational issues have been extensively studied, research into the prediction customer demand for, and the market development of, remanufactured products is still in its infancy. The majority of the existing research into remanufactured product demand is largely based on conventional statistical models that fail to capture the non-linear behaviour of customer demand and market factors in real-world business environments, in particular e-marketplaces. Therefore, this paper aims to develop a comprehensible data-mining prediction approach, in order to achieve two objectives: (1) to provide a highly accurate and robust demand prediction model of remanufactured products; and (2) to shed light on the non-linear effect of online market factors as predictors of customer demand. Based on the real-world Amazon dataset, the results suggest that predicting remanufactured product demand is a complex, non-linear problem, and that, by using advanced machine-learning techniques, our proposed approach can predict the product demand with high accuracy. In terms of practical implications, the importance of market factors is ranked according to their predictive powers of demand, while their effects on demand are analysed through their partial dependence plots. Several insights for management are revealed by a thorough comparison of the sales impact of these market factors on remanufactured and new products.〈/p〉〈/div〉

Description: We first shortly review, in part throwing a new light on, basics of ball numbers for balls having a positively homogeneous Minkowski functional and turn over then to a new particular class of ball numbers of balls having a Minkowski functional being homogeneous with respect to multiplication with a specific diagonal matrix. Applications to crystal breeding, temperature expansion and normalizing density generating functions in big data analysis are indicated and a challenging problem from the inhomogeneity program is stated.

Description: In this study, we systematically investigate a road-rail intermodal routing problem the optimization of which is oriented on the customer demands on transportation economy, timeliness and reliability. The road-rail intermodal transportation system is modelled as a hub-and-spoke network that contains time-flexible container truck services and scheduled container train services. The transportation timeliness is optimized by using fuzzy soft time windows associated with the service level of the transportation. Reliability is enhanced by considering multiple sources of time uncertainty, including road travel time and loading/unloading time. Such uncertainty is modelled by using fuzzy set theory. Triangular fuzzy numbers are adopted to represent the uncertain time. Under the above consideration, we first establish a fuzzy mixed integer nonlinear programming model with a weighted objective that includes minimizing the costs and maximizing the service level for accomplishing transportation orders. Then we use the fuzzy expected value model and fuzzy chance-constrained programming separately to realize the defuzzification of the fuzzy objective and use fuzzy chance-constrained programming to deal with the fuzzy constraint. After defuzzification and linearization, an equivalent mixed integer linear programming (MILP) model is generated to enable the problem to be solved by mathematical programming software. Finally, a numerical case modified from our previous study is presented to demonstrate the feasibility of the proposed fuzzy programming approaches. Sensitivity analysis and fuzzy simulation are comprehensively utilized to discuss the effects of the fuzzy soft time windows and time uncertainty on the routing optimization and help decision makers to better design a crisp transportation plan that can effectively make tradeoffs among economy, timeliness and reliability.

Description: We consider a class of linear inhomogeneous equations in a Banach space not solvable with respect to the fractional Caputo derivative. Such equations are called degenerate. We study the case of the existence of a resolving operators family for the respective homogeneous equation, which is an analytic in a sector. The existence of a unique solution of the Cauchy problem and of the Showalter—Sidorov problem to the inhomogeneous degenerate equation is proved. We also derive the form of the solution. The approximate controllability of infinite-dimensional control systems, described by the equations of the considered class, is researched. An approximate controllability criterion for the degenerate fractional order control system is obtained. The criterion is illustrated by the application to a system, which is described by an initial-boundary value problem for a partial differential equation, not solvable with respect to the time-fractional derivative. As a corollary of general results, an approximate controllability criterion is obtained for the degenerate fractional order control system with a finite-dimensional input.

Description: This work is concerned with the delay-dependent criteria for exponential stability analysis of neutral differential equation with a more generally interval-distributed and discrete time-varying delays. By using a novel Lyapunov–Krasovkii functional, descriptor model transformation, utilization of the Newton–Leibniz formula, and the zero equation, the criteria for exponential stability are in the form of linear matrix inequalities (LMIs). Finally, we present the effectiveness of the theoretical results in numerical examples to show less conservative conditions than the others in the literature.

Description: In this paper, we study differential equations arising from the generating function of the ( r , β ) -Bell polynomials. We give explicit identities for the ( r , β ) -Bell polynomials. Finally, we find the zeros of the ( r , β ) -Bell equations with numerical experiments.

Description: 〈p〉Publication date: Available online 9 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): N.H. Chieu, V. Jeyakumar, G. Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper we show that a convexifiability property of nonconvex quadratic programs with nonnegative variables and quadratic constraints guarantees zero duality gap between the quadratic programs and their semi-Lagrangian duals. More importantly, we establish that this convexifiability is hidden in classes of nonnegative homogeneous quadratic programs and discrete quadratic programs, such as mixed integer quadratic programs, revealing zero duality gaps. As an application, we prove that robust counterparts of uncertain mixed integer quadratic programs with objective data uncertainty enjoy zero duality gaps under suitable conditions. Various sufficient conditions for convexifiability are also given.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 9 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): C.J. Jagtenberg, A.J. Mason〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Most literature on the ambulance location problem aims to maximize coverage, i.e., the fraction of people that can be reached within a certain response time threshold. Such a problem often has one optimum, but several near-optimal solutions may exist. These may have a similar overall performance but provide different coverage for different regions. This raises the question: are we making ‘arbitrary’ choices in terms of who gets coverage and who does not? In this paper we propose to share time between several good ambulance configurations in the interest of fairness. We argue that the Bernoulli–Nash social welfare measure should be used to evaluate the fairness of the system. Therefore, we formulate a nonlinear optimization model that determines the fraction of time spent in each configuration to maximize the Bernoulli–Nash social welfare. We solve this model in a case study for an ambulance provider in the Netherlands, using a combination of simulation and optimization. Furthermore, we analyze how the Bernoulli–Nash optimal solution compares to the maximum-coverage solution by formulating and solving a multi-objective optimization model.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 9 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Jian Luo, Xin Yan, Ye Tian〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Unsupervised classification is a highly important task of machine learning methods. Although achieving great success in supervised classification, support vector machine (SVM) is much less utilized to classify unlabeled data points, which also induces many drawbacks including sensitive to nonlinear kernels and random initializations, high computational cost, unsuitable for imbalanced datasets. In this paper, to utilize the advantages of SVM and overcome the drawbacks of SVM-based clustering methods, we propose a completely new two-stage unsupervised classification method with no initialization: a new unsupervised kernel-free quadratic surface SVM (QSSVM) model is proposed to avoid selecting kernels and related kernel parameters, then a golden-section algorithm is designed to generate the appropriate classifier for balanced and imbalanced data. By studying certain properties of proposed model, a convergent decomposition algorithm is developed to implement this non-covex QSSVM model effectively and efficiently (in terms of computational cost). Numerical tests on artificial and public benchmark data indicate that the proposed unsupervised QSSVM method outperforms well-known clustering methods (including SVM-based and other state-of-the-art methods), particularly in terms of classification accuracy. Moreover, we extend and apply the proposed method to credit risk assessment by incorporating the T-test based feature weights. The promising numerical results on benchmark personal credit data and real-world corporate credit data strongly demonstrate the effectiveness, efficiency and interpretability of proposed method, as well as indicate its significant potential in certain real-world applications.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 9 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Célia Paquay, Yves Crama, Thierry Pironet〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The problem considered in this work stems from a non-profit organization in charge of door-to-door passenger transportation for medical appointments. Patients are picked up at home by a driver and are then dropped at their appointment location. They may also be driven back home at the end of their appointment. Some patients have specific requirements, e.g., they may require an accompanying person or a wheelchair. Planning such activities gives rise to a so-called dial-a-ride problem. In the present work, it is assumed that the requests assigned to the drivers have been selected, and the transportation plan has been established for the next day. However, in practice, appointment durations may vary due to unforeseen circumstances, and some transportation requests may be modified, delayed or canceled during the day. The aim of this work is to propose a reactive algorithm which can adapt the initial plan in order to manage the disruptions and to take care of as many patients as possible in real-time. The plan should be modified quickly when a perturbation is observed, without resorting to major changes which may confuse the drivers and the patients. Several recourse procedures are defined for this purpose. They allow the dispatcher to temporarily delete a request, to insert a previously deleted request, or to permanently cancel a request. Simulation techniques are used to test the approach on randomly generated scenarios. Several key performance indicators are introduced in order to measure the impact of the disruptions and the quality of the solutions.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 8 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Noémie Le Carrer, Scott Ferson, Peter L. Green〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper describes a framework that combines decision theory and stochastic optimisation techniques to address tide routing (i.e. optimisation of cargo loading and ship scheduling decisions in tidal ports and shallow seas). Unlike weather routing, tidal routing has been little investigated so far, especially from the perspective of risk analysis. Considering the journey of a bulk carrier between 〈em〉N〈/em〉 ports, a shipping decision model is designed to compute cargo loading and scheduling decisions, given the time series of the sea level point forecasts in these ports. Two procedures based on particle swarm optimisation and Monte Carlo simulations are used to solve the shipping net benefit constrained optimisation problem. The outputs of probabilistic risk minimisation are compared with those of net benefit maximisation, the latter including the possibility of a ‘rule-of-the-thumb’ safety margin. Distributional robustness is discussed as well, with respect to the modelling of sea level residuals. Our technique is assessed on two realistic case studies in British ports. Results show that the decision taking into account the stochastic dimension of sea levels is not only robust in real port and weather conditions, but also closer to optimality than standard practices using a fixed safety margin. Furthermore, it is shown that the proposed technique remains more interesting when sea level variations are artificially increased beyond the extremes of the current residual models.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 8 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Ju Zhao, Yong-Wu Zhou, Zong-Hong Cao, Jie Min〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Consider a two-echelon supply chain consisting of two manufacturers and a dominant retailer, such as big supermarkets like Walmart. Under a consignment contract with revenue sharing, the two manufacturers sell through the retailer two substitutable products whose demands are dependent on their shelf space and sales prices. The two manufacturers may compete horizontally for shelf space and pricing by three scenarios: Nash game, Stackelberg game, and collusion, and play vertically the retailer-Stackelberg game with the retailer. For each of these horizontal scenarios, we present all participators’ equilibrium strategies and their corresponding profits, based on which the impacts of manufacturers’ cost difference and moving sequence are investigated. Additionally, we discuss whether a horizontal collusion among manufacturers occurs when they choose their scenarios and whether centralization is always beneficial for the entire chain under the considered consignment contract. The study reveals the following results: (i) When the manufacturers compete horizontally, the high-cost manufacturer always sets a high-price and less shelf space strategy, while the low-cost manufacturer always adopts a low-price and more shelf space strategy, which is not affected by their moving sequence. If they collude horizontally, it is just reverse. (ii) When the two manufacturers compete horizontally, all participators’ equilibrium strategies and their corresponding profits are significantly influenced by manufacturers’ moving sequence. (iii) A horizontal collusion between the manufacturers can occur only when their cost difference is relatively small; this finding supplements existing literature. (iv) When the cost difference between manufacturers is relatively big, then centralization may be detrimental to the entire chain, which can explain why several supply chains adopt vertical competition strategies in practice. In addition, we find that these results still hold for the limited shelf space scenario and shelf-space limitation enhances the horizontal and vertical competition intensity by increasing shelf space fee.〈/p〉〈/div〉

Description: Let SR * be the class of starlike functions with real coefficients, i.e., the class of analytic functions f which satisfy the condition f ( 0 ) = 0 = f ′ ( 0 ) − 1 , Re { z f ′ ( z ) / f ( z ) } 〉 0 , for z ∈ D : = { z ∈ C : | z | 〈 1 } and a n : = f ( n ) ( 0 ) / n ! is real for all n ∈ N . In the present paper, it is obtained that the sharp inequalities − 4 / 9 ≤ H 3 , 1 ( f ) ≤ 3 / 9 hold for f ∈ SR * , where H 3 , 1 ( f ) is the third Hankel determinant of order 3 defined by H 3 , 1 ( f ) = a 3 ( a 2 a 4 − a 3 2 ) − a 4 ( a 4 − a 2 a 3 ) + a 5 ( a 3 − a 2 2 ) .

Description: 〈p〉Publication date: Available online 7 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): John H. Drake, Ahmed Kheiri, Ender Özcan, Edmund K. Burke〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Hyper-heuristics have emerged as a way to raise the level of generality of search techniques for computational search problems. This is in contrast to many approaches, which represent customised methods for a single problem domain or a narrow class of problem instances. The current state-of-the-art in hyper-heuristic research comprises a set of methods that are broadly concerned with intelligently 〈em〉selecting〈/em〉 or 〈em〉generating〈/em〉 a suitable heuristic in a given situation. Hyper-heuristics can be considered as search methods that operate on lower-level heuristics or heuristic components, and can be categorised into two main classes: heuristic selection and heuristic generation. The term hyper-heuristic was defined in the early 2000s as a 〈em〉heuristic to choose heuristics〈/em〉, but the idea of designing high-level heuristic methodologies can be traced back to the early 1960s. This paper gives a brief history of this emerging area, reviews contemporary hyper-heuristic literature, and discusses recent hyper-heuristic frameworks. In addition, the existing classification of selection hyper-heuristics is extended, in order to reflect the nature of the challenges faced in contemporary research. Unlike the survey on hyper-heuristics published in 2013, this paper focuses only on selection hyper-heuristics and presents critical discussion, current research trends and directions for future research.〈/p〉〈/div〉

Description: We consider the extreme value problem of the minimum-maximum models for the independent and identically distributed random sequence and stationary random sequence, respectively. By invoking some probability formulas and Taylor’s expansions of the distribution functions, the limiting distributions for these two kinds of sequences are obtained. Moreover, convergence analysis is carried out for those extreme value distributions. Several numerical experiments are conducted to validate our theoretical results.

Description: 〈p〉Publication date: Available online 6 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Sana Dahmen, Monia Rekik, François Soumis, Guy Desaulniers〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we address a personalized multi-department multi-day shift scheduling problem with a multi-skill heterogeneous workforce where employees can be transferred between departments under some restrictions. The objective is to construct a schedule that minimizes under-coverage, over-coverage, transfer and labor costs. We propose a novel two-stage approach to solve it: the first stage considers an approximate and smaller problem based on data aggregation and produces approximate transfers. The second stage constructs personalized schedules based on the information deduced from the first stage. An exhaustive experimental study is conducted and proves the efficiency of the proposed approach in terms of solution quality and computing times.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 5 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Peter Nystrup, Erik Lindström, Pierre Pinson, Henrik Madsen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We propose four different estimators that take into account the autocorrelation structure when reconciling forecasts in a temporal hierarchy. Combining forecasts from multiple temporal aggregation levels exploits information differences and mitigates model uncertainty, while reconciliation ensures a unified prediction that supports aligned decisions at different horizons. In previous studies, weights assigned to the forecasts were given by the structure of the hierarchy or the forecast error variances without considering potential autocorrelation in the forecast errors. Our first estimator considers the autocovariance matrix within each aggregation level. Since this can be difficult to estimate, we propose a second estimator that blends autocorrelation and variance information, but only requires estimation of the first-order autocorrelation coefficient at each aggregation level. Our third and fourth estimators facilitate information sharing between aggregation levels using robust estimates of the cross-correlation matrix and its inverse. We compare the proposed estimators in a simulation study and demonstrate their usefulness through an application to short-term electricity load forecasting in four price areas in Sweden. We find that by taking account of auto- and cross-covariances when reconciling forecasts, accuracy can be significantly improved uniformly across all frequencies and areas.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 5 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Bowei Chen, Jingmin Huang, Yufei Huang, Stefanos Kollias, Shigang Yue〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉While page views are often sold instantly through real-time auctions when users visit websites, they can also be sold in advance via guaranteed contracts. In this paper, we present a dynamic programming model to study how an online publisher should optimally allocate and price page views between guaranteed and spot markets. The problem is challenging because the allocation and pricing of guaranteed contracts affect how advertisers split their purchases between the two markets, and the terminal value of the model is endogenously determined by the updated dual force of supply and demand in auctions. We take the advertisers’ purchasing behaviour into consideration, i.e., risk aversion and stochastic demand arrivals, and present a scalable and efficient algorithm for the optimal solution. The model is also empirically validated with a commercial dataset. The experimental results show that selling page views via both channels can increase the publisher’s expected total revenue, and the optimal pricing and allocation strategies are robust to different market and advertiser types.〈/p〉〈/div〉

Description: In this paper, we offer a new approach of investigation and approximation of solutions of Caputo-type fractional differential equations under nonlinear boundary conditions. By using an appropriate parametrization technique, the original problem with nonlinear boundary conditions is reduced to the equivalent parametrized boundary-value problem with linear restrictions. To study the transformed problem, we construct a numerical-analytic scheme which is successful in relation to different types of two-point and multipoint linear boundary and nonlinear boundary conditions. Moreover, we give sufficient conditions of the uniform convergence of the successive approximations. Also, it is indicated that these successive approximations uniformly converge to a parametrized limit function and state the relationship of this limit function and exact solution. Finally, an example is presented to illustrate the theory.

Description: In this paper, we focus on studying the split feasibility problem (SFP) in Hilbert spaces. Based on the CQ algorithm involving the self-adaptive technique, we introduce a three-step iteration process for approximating the solution of SFP. Then, the convergence results are established under mild conditions. Numerical experiments are provided to show the efficiency in signal processing. Some comparisons to various methods are also provided in this paper.

Description: We investigate the split variational inclusion problem in Hilbert spaces. We propose efficient algorithms in which, in each iteration, the stepsize is chosen self-adaptive, and proves weak and strong convergence theorems. We provide numerical experiments to validate the theoretical results for solving the split variational inclusion problem as well as the comparison to algorithms defined by Byrne et al. and Chuang, respectively. It is shown that the proposed algorithms outrun other algorithms via numerical experiments. As applications, we apply our method to compressed sensing in signal recovery. The proposed methods have as a main advantage that the computation of the Lipschitz constants for the gradient of functions is dropped in generating the sequences.

Description: 〈p〉Publication date: Available online 6 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): M. Van Den Eeckhout, M. Vanhoucke, B. Maenhout〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The personnel staffing problem calculates the required workforce size and is determined by constructing a baseline personnel roster that assigns personnel members to duties in order to cover certain staffing requirements. In this research, we incorporate the planning of the duty demand in the staff scheduling problem in order to lower the staffing costs. More specifically, the demand originates from a project scheduling problem with discrete time/resource trade-offs, which embodies additional flexibility as activities can be executed in different modes. In order to tackle this integrated problem, we propose a decomposed branch-and-price procedure. A tight lower and upper bound are calculated using a problem formulation that models the project scheduling constraints and the time-related resource scheduling constraints implicitly in the decision variables. Based upon these bounds, the strategic problem is decomposed into multiple tactical subproblems with a fixed workforce size and an optimal solution is searched for each subproblem via branch-and-price. Fixing the workforce size in a subproblem facilitates the definition of resource capacity cuts, which limit the set of eligible project schedules, decreasing the size of the branching tree. In addition, in order to find the optimal integer solution, we propose a specific search strategy based upon the lower bound and dedicated rules to branch upon the workload generated by a project schedule. The computational results show that applying the proposed search space decomposition and the inclusion of resource capacity cuts lead to a well-performing procedure outperforming different other heuristic and exact methodologies.〈/p〉〈/div〉

Description: The aim of this paper is the approximation of nonlinear equations using iterative methods. We present a unified convergence analysis for some two-point type methods. This way we compare specializations of our method using not necessarily the same convergence criteria. We consider both semilocal and local analysis. In the first one, the hypotheses are imposed on the initial guess and in the second on the solution. The results can be applied for smooth and nonsmooth operators.

Description: Let K be a field and let S = K [ x 1 , ⋯ , x n ] be a polynomial ring over K. We analyze the extremal Betti numbers of special squarefree monomial ideals of S known as the t-spread strongly stable ideals, where t is an integer ≥ 1 . A characterization of the extremal Betti numbers of such a class of ideals is given. Moreover, we determine the structure of the t-spread strongly stable ideals with the maximal number of extremal Betti numbers when t = 2 .

Description: The flexible job shop scheduling problem (FJSP) is a difficult discrete combinatorial optimization problem, which has been widely studied due to its theoretical and practical significance. However, previous researchers mostly emphasized on the production efficiency criteria such as completion time, workload, flow time, etc. Recently, with considerations of sustainable development, low-carbon scheduling problems have received more and more attention. In this paper, a low-carbon FJSP model is proposed to minimize the sum of completion time cost and energy consumption cost in the workshop. A new bio-inspired metaheuristic algorithm called discrete whale optimization algorithm (DWOA) is developed to solve the problem efficiently. In the proposed DWOA, an innovative encoding mechanism is employed to represent two sub-problems: Machine assignment and job sequencing. Then, a hybrid variable neighborhood search method is adapted to generate a high quality and diverse population. According to the discrete characteristics of the problem, the modified updating approaches based on the crossover operator are applied to replace the original updating method in the exploration and exploitation phase. Simultaneously, in order to balance the ability of exploration and exploitation in the process of evolution, six adjustment curves of a are used to adjust the transition between exploration and exploitation of the algorithm. Finally, some well-known benchmark instances are tested to verify the effectiveness of the proposed algorithms for the low-carbon FJSP.

Description: This paper puts forward an innovative theory and method to calculate the canonical labelings of graphs that are distinct to N a u t y ’s. It shows the correlation between the canonical labeling of a graph and the canonical labeling of its complement graph. It regularly examines the link between computing the canonical labeling of a graph and the canonical labeling of its o p e n k- n e i g h b o r h o o d s u b g r a p h . It defines d i f f u s i o n d e g r e e s e q u e n c e s and e n t i r e d i f f u s i o n d e g r e e s e q u e n c e . For each node of a graph G, it designs a characteristic m _ N e a r e s t N o d e to improve the precision for calculating canonical labeling. Two theorems established here display how to compute the first nodes of M a x Q ( G ) . Another theorem presents how to determine the second nodes of M a x Q ( G ) . When computing C m a x ( G ) , if M a x Q ( G ) already holds the first i nodes u 1 , u 2 , ⋯ , u i , Diffusion and Nearest Node theorems provide skill on how to pick the succeeding node of M a x Q ( G ) . Further, it also establishes two theorems to determine the C m a x ( G ) of disconnected graphs. Four algorithms implemented here demonstrate how to compute M a x Q ( G ) of a graph. From the results of the software experiment, the accuracy of our algorithms is preliminarily confirmed. Our method can be employed to mine the frequent subgraph. We also conjecture that if there is a node v ∈ S ( G ) meeting conditions C m a x ( G − v ) ⩽ C m a x ( G − w ) for each w ∈ S ( G ) ∧ w ≠ v , then u 1 = v for M a x Q ( G ) .

Description: 〈p〉Publication date: Available online 28 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 European Journal of Operational Research〈/p〉 〈p〉Author(s): Javier Duran-Micco, Evert Vermeir, Pieter Vansteenwegen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Urban transportation contributes significantly to CO〈sub〉2〈/sub〉 emissions. Public transport systems are a good strategy to reduce these, but the emissions generated by public transport vehicles should not be neglected during the design of the service. The Transit Network Design and Frequency Setting Problem (TNDFSP) has usually been addressed considering only the passengers’ and the operator's point of view. However, we show it is worthwhile to consider also the emissions already during this planning phase.〈/p〉 〈p〉This paper proposes a memetic algorithm to address the bi-objective TNDFSP where both the total travel time and the CO〈sub〉2〈/sub〉 emissions are minimized. The analysis considers a heterogeneous fleet, meaning that buses of different sizes and technologies can be assigned under a budget constraint. The results on benchmark instances show that the proposed memetic algorithm performs as well as state-of-the-art algorithms where CO〈sub〉2〈/sub〉 emissions are not considered. In addition, several experiments are carried out to observe the effect of incorporating emissions and heterogeneous fleet into the model. The heterogeneous fleet allows reducing travel times and emissions at the same time, compared to solutions without a heterogeneous fleet. Moreover, the explicit minimization of CO〈sub〉2〈/sub〉 emissions within a bi-objective framework allows illustrating the trade-off between both objectives. Reductions of about 30% in the emissions can be achieved by increasing the travel time only 1%, while the costs for the operator remain the same. This clearly demonstrates the benefits of considering both the CO〈sub〉2〈/sub〉 emissions and a heterogeneous fleet during the design stage of public transport systems.〈/p〉 〈/div〉

Description: In this paper, we introduce the various types of generalized invexities, i.e., α f -invex/ α f -pseudoinvex and ( G , α f ) -bonvex/ ( G , α f ) -pseudobonvex functions. Furthermore, we construct nontrivial numerical examples of ( G , α f ) -bonvexity/ ( G , α f ) -pseudobonvexity, which is neither α f -bonvex/ α f -pseudobonvex nor α f -invex/ α f -pseudoinvex with the same η . Further, we formulate a pair of second-order non-differentiable symmetric dual models and prove the duality relations under α f -invex/ α f -pseudoinvex and ( G , α f ) -bonvex/ ( G , α f ) -pseudobonvex assumptions. Finally, we construct a nontrivial numerical example justifying the weak duality result presented in the paper.

Description: In this article, we discuss new characterizations of Cohen-Macaulay bipartite edge ideals. For arbitrary bipartite edge ideals I ( G ) , we also discuss methods to recognize regular elements on I ( G ) s for all s ≥ 1 in terms of the combinatorics of the graph G.