ALBERT

Beschreibung: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 133〈/p〉 〈p〉Author(s): Renchao Liang, Junwei Wang, Min Huang, Zhong-Zhong Jiang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Auctions are an important method for solving the logistics procurement problem in electronics markets. However, current auction methods rarely consider the existence of quantity discounts. To fill this research gap, we introduce quantity discounts into the procurement Vickrey–Clark–Groves (P-VCG) and truthful double-auction mechanisms and apply them to the logistics services procurement market. For a market with only one customer, we design a P-VCG auction with quantity discounts, and for a market with multiple customers, we construct a model for maximizing social welfare and propose a trade reduction with a quantity discount (TR-QD) double-auction mechanisms. We prove that both auction mechanisms ensure incentive compatibility, individual rationality, balanced budget, and asymptotical efficiency. Furthermore, compared with traditional truthful double-auctions, the TR-QD mechanism supports cooperative purchases—which allows more customers to enjoy discounts on large-scale logistics services—and bid time priority—which achieves the goal of meeting earlier requests earlier and improves auction efficiency. Numerical studies further show that the TR-QD auction mechanism can achieve an increase in customers’ total value, logistics companies’ total value, social welfare and total trading volume.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 133〈/p〉 〈p〉Author(s): David Torres Sanchez, Burak Boyacı, Konstantinos G. Zografos〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Fierce competition between airlines has led to the need of minimising the operating costs while also ensuring quality of service. Given the large proportion of operating costs dedicated to aircraft maintenance, cooperation between airlines and their respective maintenance provider is paramount. In this research, we propose a framework to develop commercially viable and maintenance feasible flight and maintenance schedules. Such framework involves two multi-objective mixed integer linear programming (MMILP) formulations and an iterative algorithm. The first formulation, the airline fleet maintenance scheduling (AMS) with violations, minimises the number of maintenance regulation violations and the number of not airworthy aircraft; subject to limited workshop resources and current maintenance regulations on individual aircraft flying hours. The second formulation, the AMS with tail assignment (TA) allows aircraft to be assigned to different flights. In this case, subject to similar constraints as the first formulation, six lexicographically ordered objective functions are minimised. Namely, the number of violations, maximum resource level, number of tail reassignments, number of maintenance interventions, overall resource usage, and the amount of maintenance required by each aircraft at the end of the planning horizon. The iterative algorithm ensures fast computational times while providing good quality solutions. Additionally, by tracking aircraft and using precise flying hours between maintenance opportunities, we ensure that the aircraft are airworthy at all times. Computational tests on real flight schedules over a 30-day planning horizon show that even with multiple airlines and workshops (16000 flights, 529 aircraft, 8 maintenance workshops), our solution approach can construct near-optimal maintenance schedules within minutes.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 133〈/p〉 〈p〉Author(s): Songpo Yang, Feixiong Liao, Jianjun Wu, Harry J.P. Timmermans, Huijun Sun, Ziyou Gao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Complex passenger demand and electricity transmission processes in metro systems cause difficulties in formulating optimal timetables and train speed profiles, often leading to inefficiency in energy consumption and passenger service. Based on energy-regenerative technologies and smart-card data, this study formulates an optimization model incorporating energy allocation and passenger assignment to balance energy use and passenger travel time. The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is applied and the core components are redesigned to obtain an efficient Pareto frontier of irregular timetables for maximizing the use of regenerative energy and minimizing total travel time. Particularly, a parallelogram-based method is developed to generate random feasible timetables; crossover and local-search-driven mutation operators are proposed relying on the graphic representations of the domain knowledge. The suggested approach is illustrated using real-world data of a bi-directional metro line in Beijing. The results show that the approach significantly improves regenerative energy use and reduces total travel time compared to the fixed regular timetable.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 133〈/p〉 〈p〉Author(s): Subodh Dubey, Prateek Bansal, Ricardo A. Daziano, Erick Guerra〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In multinomial response models, idiosyncratic variations in the indirect utility are generally modeled using Gumbel or normal distributions. This study makes a strong case to substitute these thin-tailed distributions with a t-distribution. First, we demonstrate that a model with a t-distributed error kernel better estimates and predicts preferences, especially in class-imbalanced datasets. Our proposed specification also implicitly accounts for decision-uncertainty behavior, i.e. the degree of certainty that decision-makers hold in their choices relative to the variation in the indirect utility of any alternative. Second – after applying a t-distributed error kernel in a multinomial response model for the first time – we extend this specification to a generalized continuous-multinomial (GCM) model and derive its full-information maximum likelihood estimation procedure. The likelihood involves an open-form expression of the cumulative density function of the multivariate t-distribution, which we propose to compute using a combination of the composite marginal likelihood method and the separation-of-variables approach. Third, we establish finite sample properties of the GCM model with a t-distributed error kernel (GCM-t) and highlight its superiority over the GCM model with a normally-distributed error kernel (GCM-N) in a Monte Carlo study. Finally, we compare GCM-t and GCM-N in an empirical setting related to preferences for electric vehicles (EVs). We observe that accounting for decision-uncertainty behavior in GCM-t results in lower elasticity estimates and a higher willingness to pay for improving the EV attributes than those of the GCM-N model. These differences are relevant in making policies to expedite the adoption of EVs.〈/p〉〈/div〉

Beschreibung: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 134〈/p〉 〈p〉Author(s): Jian Sun, Jiyan Wu, Feng Xiao, Ye Tian, Xiangdong Xu〈/p〉

Beschreibung: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 134〈/p〉 〈p〉Author(s): Chuntian Zhang, Yuan Gao, Lixing Yang, Ziyou Gao, Jianguo Qi〈/p〉

Beschreibung: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 133〈/p〉 〈p〉Author(s): 〈/p〉

Beschreibung: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 134〈/p〉 〈p〉Author(s): Edison Avraham, Tal Raviv〈/p〉