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  • Articles  (58)
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  • linear programming  (58)
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  • 1995-1999  (35)
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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    OR spectrum 19 (1997), S. 147-157 
    ISSN: 1436-6304
    Keywords: Key words: production ; scheduling ; printed circuit board assembly ; modelling ; linear programming ; aggregational error ; decision support ; Schlüsselwörter: Produktion ; Ablaufplanung ; Leiterplattenbestückung ; Modellierung ; lineare Programmierung ; Aggregationsfehler ; Entscheidungsunterstützung ; S′jm = Sjm ; SFj(r)(12)
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Description / Table of Contents: Zusammenfassung. Bei der Kleinserienmontage von Leiterplatten besteht das Problem der Einlastungsplanung darin, ein Tagesprogramm an Produktionsaufträgen zusammenzustellen, die gemeinsam in das Produktionssystem eingeschleust werden. Jeder Produktionsauftrag entspricht einem bestimmten Leiterplattentyp. Wechselt man bei der automatischen Bestückung von Leiterplatten zu einem neuen Leiterplattentyp, so fallen erhebliche Rüstzeiten an, die davon abhängen, wie viele Bauteilezuführungen im Magazin der Bestückungsautomaten ausgewechselt werden müssen. Zur Unterstützung dieses Entscheidungsproblems werden zwei unterschiedliche Modelle der linearen Optimierung entwickelt. Die beiden Modelle unterscheiden sich vor allem durch ihren Aggregationsgrad und ihren Rechenaufwand. Zur Verringerung des Aggregationsfehlers wird ein auf der Fuzzy-Set-Theorie beruhender Ansatz zur Abschätzung der bei automatischen SMD-Bestückungsautomanten auftretenden Rüstzeiten entwickelt. Hierbei wird als industrielles Anwendungsbeispiel die Leiterplattenbestückung in einem bedeutenden Elektronikunternehmen betrachtet. Die durchgeführte numerische Untersuchung zeigt, daß das hochaggregierte Fuzzy-LP-Modell zu hinreichend genauen Lösungen führt und erheblich geringeren Rechenaufwand verursacht als ein detaillierteres LP-Modell. Außerdem wird die praktische Eignung des Fuzzy-LP-Modells für den Einsatz innerhalb eines interaktiven Entscheidungsunterstützungssystems verdeutlicht.
    Notes: Abstract. The problem of workload planning in small lot printed circuit board (PCB) assembly concerns the determination of the daily mix of production orders to be released into the production system. When switching from one production order (board type) to another, a considerable set-up time is incurred based on the number of component feeders to be replaced in the component magazine of the assembly machines. To support the order-mix decision faced by a major electronics manufacturer, two versions of a linear programming model are developed. The models differ primarily in their degree of aggregation and their computational effort. In order to reduce the aggregational error incurred, a fuzzy approach is developed to estimate the number of component set-ups at automatic SMD placement machines. Our numerical investigation reveals that sufficiently accurate solutions may be obtained from a highly aggregate fuzzy LP-model and this is achieved with considerably less computational effort than with a more detailed LP-model. We also demonstrate the potential suitability of the fuzzy LP-model for implementation within an interactive decision support system.
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  • 2
    Electronic Resource
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    OR spectrum 19 (1997), S. 147-157 
    ISSN: 1436-6304
    Keywords: production ; scheduling ; printed circuit board assembly ; modelling ; linear programming ; aggregational error ; decision support ; Produktion ; Ablaufplanung ; Leiterplattenbestückung ; Modellierung ; lineare Programmierung ; Aggregationsfehler ; Entscheidungsunterstützung
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Description / Table of Contents: Zusammenfassung Bei der Kleinserienmontage von Leiterplatten besteht das Problem der Einlastungsplanung darin, ein Tagesprogramm an Produktionsaufträgen zusammenzustellen, die gemeinsam in das Produktionssystem eingeschleust werden. Jeder Produktionsauftrag entspricht einem bestimmten Leiterplattentyp. Wechselt man bei der automatischen Bestückung von Leiterplatten zu einem neuen Leiterplattentyp, so fallen erhebliche Rüstzeiten an, die davon abhängen, wie viele Bauteilezuführungen im Magazin der Bestückungsautomaten ausgewechselt werden müssen. Zur Unterstützung dieses Entscheidungsproblems werden zwei unterschiedliche Modelle der linearen Optimierung entwickelt. Die beiden Modelle unterscheiden sich vor allem durch ihren Aggregationsgrad und ihren Rechenaufwand. Zur Verringerung des Aggregationsfehlers wird ein auf der Fuzzy-Set-Theorie beruhender Ansatz zur Abschätzung der bei automatischen SMD-Bestückungsautomanten auftretenden Rüstzeiten entwickelt. Hierbei wird als industrielles Anwendungsbeispiel die Leiterplattenbestückung in einem bedeutenden Elektronikunternehmen betrachtet. Die durchgeführte numerische Untersuchung zeigt, daß das hochaggregierte Fuzzy-LP-Modell zu hinreichend genauen Lösungen führt und erheblich geringeren Rechenaufwand verursacht als ein detaillierteres LP-Modell. Außerdem wird die praktische Eignung des Fuzzy-LP-Modells für den Einsatz innerhalb eines interaktiven Entscheidungsunterstützungssystems verdeutlicht.
    Notes: Abstract The problem of workload planning in small lot printed circuit board (PCB) assembly concerns the determination of the daily mix of production orders to be released into the production system. When switching from one production order (board type) to another, a considerable set-up time is incurred based on the number of component feeders to be replaced in the component magazine of the assembly machines. To support the order-mix decision faced by a major electronics manufacturer, two versions of a linear programming model are developed. The models differ primarily in their degree of aggregation and their computational effort. In order to reduce the aggregational error incurred, a fuzzy approach is developed to estimate the number of component set-ups at automatic SMD placement machines. Our numerical investigation reveals that sufficiently accurate solutions may be obtained from a highly aggregate fuzzy LP-model and this is achieved with considerably less computational effort than with a more detailed LP-model. We also demonstrate the potential suitability of the fuzzy LP-model for implementation within an interactive decision support system.
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  • 3
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    OR spectrum 17 (1995), S. 41-50 
    ISSN: 1436-6304
    Keywords: Energy-Emission Modelling ; linear programming ; international environmental policy ; emission reduction strategies ; Energie-Emissions-Modellierung ; lineare Programmierung ; internationale Umweltpolitik ; sionsminderungsstrategien
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Description / Table of Contents: Zusammenfassung Diese Arbeit gibt einen Überblick über methodische Ansätze zur Herleitung nationaler und internationaler Emissionsminderungsstrategien. Zu diesem Zweck werden häufig sogenannte integrierte Energie-Emissions-Modelle (lineare Programme) eingesetzt. Das EG-EFOM-ENV Modell wird vorgestellt und seine prinzipielle Anwendung aufgezeigt. Konkrete Ergebnisse werden anhand des Beispiels Litauens angegeben. Einschränkungen der verwendeten Methodik sowie deren mögliche Erweiterungen werden diskutiert.
    Notes: Abstract This paper provides an insight into the elaboration of strategies for emission reduction at present internationally requested by applying energy-emission models. One of these models, the EC-EFOM-ENV LP-model is presented in detail. Its application is shown in principle as well as to the special situation of countries in transition from a centrally planned to a market economy. The limitations of this approach and further applications on an international level are assessed.
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  • 4
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    OR spectrum 18 (1996), S. 131-144 
    ISSN: 1436-6304
    Keywords: Cutting stock ; integer solutions ; heuristics ; linear programming ; column generation ; numerical experiments ; Zuschneideprobleme ; Ganzzahligkeit ; Heuristiken ; Lineare Optimierung ; Spaltengenerierung ; Numerische Experimente
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Description / Table of Contents: Zusammenfassung In der vorliegenden Arbeit betrachten wir das Problem der Bestimmung ganzzahliger Lösungen für das Standardproblem der eindimensionalen Zuschnittplanung. Insbesondere werden eine spezielle Klasse heuristischer Lösungsverfahren, die in der Literatur beschrieben sind, sowie einige naheliegende Varianten dieser Verfahren vorgestellt. Auf der Grundlage eines numerischen Experiments, bei dem 4.000 Probleme zufällig erzeugt und gelöst wurden, werden die Verfahren miteinander verglichen und im Hinblick auf die Kriterien „Lösungsqualität“ und „Rechenzeitbedarf“ beurteilt. Dabei zeigt sich nicht nur, daß zwei Verfahren deutlich besser als die übrigen einzustufen sind, sondern auch, daß mit ihrer Hilfe nahezu jede Problemausprägung des klassischen eindimensionalen Zuschneideproblems optimal gelöst werden kann.
    Notes: Abstract In this paper the problem of generating integer solutions to the standard one-dimensional cutting stock problem is treated. In particular, we study a specific class of heuristic approaches that have been proposed in the literature, and some straightforward variants. These methods are compared with respect to solution quality and computing time. Our evaluation is based on having solved 4,000 randomly generated test problems. Not only will it be shown that two methods are clearly superior to the others but also that they solve almost any instance of the standard one-dimensional cutting stock problem to an optimum.
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  • 5
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    OR spectrum 19 (1997), S. 67-74 
    ISSN: 1436-6304
    Keywords: Deckung des Bedarfs an Klassenräumen ; lineare Optimierung ; gemischt ganzzahlige Optimierung ; Covering classroom requirements ; linear programming ; mixed integer programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Description / Table of Contents: Abstract The city of Hamburg expects for the next years enormously increasing rates of pupils. Covering the additional need of classrooms by new building is very expensive. It would be better to avoid this by making good use of the existing resources. The possible steps for covering the requirements and the restrictions are explained subsequently. There are a lot of alternatives, which must be coordinated for a “good” solution in a suitable way. The mathematical model for this problem is described furthermore. The model in question belongs to the class of mixed integer problems. Finally the standard optimization software SCICONIC, which is used for solving the mixed integer problem, is introduced and the embedding of SCICONIC into the architecture of the evolved planning system is described. Because the users of the system are officers without knowledge in electronic data processing and mathematical programming, a user friendly interface is of special importance in this case. This paper does not include new mathematical cognition, but describes the skilled use of known OR-techniques in a real software project.
    Notes: Zusammenfassung Die Stadt Hamburg sieht in den nächsten Jahren eine beträchtliche Schülerwelle auf sich zukommen. Daraus resultiert zusätzlicher Klassenraumbedarf, der durch Neubau nur sehr kostspielig gedeckt werden kann. Durch systematische Ausnutzung von bestehenden Raumreserven lassen sich teure Neubaumaßnahmen weitgehend vermeiden. Im folgenden werden zunächst die möglichen Maßnahmen zur Raumbedarfsdeckung mit ihren einschränkenden Bedingungen aufgezeigt. Die Maßnahmen erlauben eine Vielzahl von Handlungsalternativen, die zum wirksamen Einsatz optimal aufeinander abgestimmt werden müssen. Das mathematische Modell zur Lösung dieses Problems wird in der weiteren Folge beschrieben. Es handelt sich um ein gemischt ganzzahliges Optimierungsproblem. Abschließend wird die zur Lösung eingesetzte Standard-Optimierungs-Software SCICONIC vorgestellt und die Einbindung von SCICONIC in das entwickelte Raumplanungssystem geschildert. Da die Anwender des Systems Sachbearbeiter ohne DV- und OR-Erfahrung sind, hat hier Benutzerfreundlichkeit eine besonders hohe Bedeutung. Der vorliegende Aufsatz erhebt nicht den Anspruch auf neue mathematische Erkenntnisse, sondern er beschreibt die fachgerechte Anwendung bekannter OR-Verfahren in einem Software-Projekt der Praxis.
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  • 6
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    OR spectrum 19 (1997), S. 67-74 
    ISSN: 1436-6304
    Keywords: Schlüsselwörter: Deckung des Bedarfs an Klassenräumen ; lineare Optimierung ; gemischt ganzzahlige Optimierung ; Key words: Covering classroom requirements ; linear programming ; mixed integer programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Description / Table of Contents: Abstract. The city of Hamburg expects for the next years enormously increasing rates of pupils. Covering the additional need of classrooms by new building is very expensive. It would be better to avoid this by making good use of the existing resources. The possible steps for covering the requirements and the restrictions are explained subsequently. There are a lot of alternatives, which must be coordinated for a ``good'' solution in a suitable way. The mathematical model for this problem is described furthermore. The model in question belongs to the class of mixed integer problems. Finally the standard optimization software SCICONIC, which is used for solving the mixed integer problem, is introduced and the embedding of SCICONIC into the architecture of the evolved planning system is described. Because the users of the system are officers without knowledge in electronic data processing and mathematical programming, a user friendly interface is of special importance in this case. This paper does not include new mathematical cognition, but describes the skilled use of known OR-techniques in a real software project.
    Notes: Zusammenfassung. Die Stadt Hamburg sieht in den nächsten Jahren eine beträchtliche Schülerwelle auf sich zukommen. Daraus resultiert zusätzlicher Klassenraumbedarf, der durch Neubau nur sehr kostspielig gedeckt werden kann. Durch systematische Ausnutzung von bestehenden Raumreserven lassen sich teure Neubaumaßnahmen weitgehend vermeiden. Im folgenden werden zunächst die möglichen Maßnahmen zur Raumbedarfsdeckung mit ihren einschränkenden Bedingungen aufgezeigt. Die Maßnahmen erlauben eine Vielzahl von Handlungsalternativen, die zum wirksamen Einsatz optimal aufeinander abgestimmt werden müssen. Das mathematische Modell zur Lösung dieses Problems wird in der weiteren Folge beschrieben. Es handelt sich um ein gemischt ganzzahliges Optimierungsproblem. Abschließend wird die zur Lösung eingesetzte Standard-Optimierungs-Software SCICONIC vorgestellt und die Einbindung von SCICONIC in das entwickelte Raumplanungssystem geschildert. Da die Anwender des Systems Sachbearbeiter ohne DV- und OR-Erfahrung sind, hat hier Benutzerfreundlichkeit eine besonders hohe Bedeutung. Der vorliegende Aufsatz erhebt nicht den Anspruch auf neue mathematische Erkenntnisse, sondern er beschreibt die fachgerechte Anwendung bekannter OR-Verfahren in einem Software-Projekt der Praxis.
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  • 7
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    Mathematical programming 43 (1989), S. 151-173 
    ISSN: 1436-4646
    Keywords: Conical projection methods ; Karmarkar's LP algorithm ; linear programming ; poly-nomial-time algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The Linear Programming Problem is manipulated to be stated as a Non-Linear Programming Problem in which Karmarkar's logarithmic potential function is minimized in the positive cone generated by the original feasible set. The resulting problem is then solved by a master algorithm that iteratively rescales the problem and calls an internal unconstrained non-linear programming algorithm. Several different procedures for the internal algorithm are proposed, giving priority either to the reduction of the potential function or of the actual cost. We show that Karmarkar's algorithm is equivalent to this method in the special case in which the internal algorithm is reduced to a single steepest descent iteration. All variants of the new algorithm have the same complexity as Karmarkar's method, but the amount of computation is reduced by the fact that only one projection matrix must be calculated for each call of the internal algorithm.
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  • 8
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    Mathematical programming 41 (1988), S. 317-325 
    ISSN: 1436-4646
    Keywords: Parametric methods ; linear programming ; anti-cycling pivoting rules
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The traditional perturbation (or lexicographic) methods for resolving degeneracy in linear programming impose decision rules that eliminate ties in the simplex ratio rule and, therefore, restrict the choice of exiting basic variables. Bland's combinatorial pivoting rule also restricts the choice of exiting variables. Using ideas from parametric linear programming, we develop anticycling pivoting rules that do not limit the choice of exiting variables beyond the simplex ratio rule. That is, any variable that ties for the ratio rule can leave the basis. A similar approach gives pivoting rules for the dual simplex method that do not restrict the choice of entering variables.
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  • 9
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    Mathematical programming 42 (1988), S. 125-133 
    ISSN: 1436-4646
    Keywords: Cycling ; degeneracy ; graph theory ; linear programming ; sensitivity analysis ; simplex method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
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  • 10
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    Mathematical programming 40 (1988), S. 165-181 
    ISSN: 1436-4646
    Keywords: Relaxation ; network ; integer programming ; linear programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The strategy of subdividing optimization problems into layers by splitting variables into multiple copies has proved useful as a method for inducing exploitable structure in a variety of applications, particularly those involving embedded pure and generalized networks. A framework is proposed in this paper which leads to new relaxation and restriction methods for linear and integer programming based on our extension of this strategy. This framework underscores the use of constructions that lead to stronger relaxations and more flexible strategies than previous applications. Our results establish the equivalence of all layered Lagrangeans formed by parameterizing the equal value requirement of copied variables for different choices of the principal layers. It is further shown that these Lagrangeans dominate traditional Lagrangeans based on incorporating non-principal layers into the objective function. In addition a means for exploiting the layered Lagrangeans is provided by generating subgradients based on a simple averaging calculation. Finally, we show how this new layering strategy can be augmented by an integrated relaxation/restriction procedure, and indicate variations that can be employed to particular advantage in a parallel processing environment. Preliminary computational results on fifteen real world zero-one personnel assignment problems, comparing two layering approaches with five procedures previously found best for those problems, are encouraging. One of the layering strategies tested dominated all non-layering procedures in terms of both quality and solution time.
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  • 11
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    Annals of operations research 5 (1985), S. 599-612 
    ISSN: 1572-9338
    Keywords: Microcomputers ; spreadsheets ; linear programming ; optimization ; software
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract This paper discusses the advantages of using spreadsheets for problem specification and report generation in optimization projects. It summarizes some of the mathematical programming software which is compatible with popular spreadsheets. A small production planning problem is used to illustrate the steps in input and processing of the results. Two programs are compared in detail.
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  • 12
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    Annals of operations research 14 (1988), S. 41-59 
    ISSN: 1572-9338
    Keywords: Parallel algorithms ; SOR ; gradient projection ; linear programming ; linear complementarity problem
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract A gradient projection successive overrelaxation (GP-SOR) algorithm is proposed for the solution of symmetric linear complementary problems and linear programs. A key distinguishing feature of this algorithm is that when appropriately parallelized, the relaxation factor interval (0, 2) isnot reduced. In a previously proposed parallel SOR scheme, the substantially reduced relaxation interval mandated by the coupling terms of the problem often led to slow convergence. The proposed parallel algorithm solves a general linear program by finding its least 2-norm solution. Efficiency of the algorithm is in the 50 to 100 percent range as demonstrated by computational results on the CRYSTAL token-ring multicomputer and the Sequent Balance 21000 multiprocessor.
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  • 13
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    Annals of operations research 58 (1995), S. 519-531 
    ISSN: 1572-9338
    Keywords: Driver scheduling ; multiple objectives ; linear programming ; dual simplex
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract A Mathematical Programming model of a driver scheduling system is described. This consists of set covering and partitioning constraints, possibly user-supplied side constraints, and two pre-emptively ordered objectives. The previous solution strategy addressed the two objectives using separate Primal Simplex optimisations; a new strategy uses a single weighted objective function and a Dual Simplex algorithm initiated by a specially developed heuristic. Computational results are reported.
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  • 14
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    Annals of operations research 62 (1996), S. 419-437 
    ISSN: 1572-9338
    Keywords: Big-M Phase I procedure ; convex quadratic programming ; interior point methods ; linear programming ; method of centers ; multidirectional search direction ; nonconvex quadratic programming ; recentering
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract In this paper, we present an interior point algorithm for solving both convex and nonconvex quadratic programs. The method, which is an extension of our interior point work on linear programming problems efficiently solves a wide class of largescale problems and forms the basis for a sequential quadratic programming (SQP) solver for general large scale nonlinear programs. The key to the algorithm is a three-dimensional cost improvement subproblem, which is solved at every interation. We have developed an approximate recentering procedure and a novel, adaptive big-M Phase I procedure that are essential to the sucess of the algorithm. We describe the basic method along with the recentering and big-M Phase I procedures. Details of the implementation and computational results are also presented.
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  • 15
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    Annals of operations research 64 (1996), S. 197-210 
    ISSN: 1572-9338
    Keywords: Feasibility ; uncapacitated network ; Gale-Hoffman inequality ; linear programming ; frame ; cut ; facet ; polar matrix
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract The purpose of this paper is to investigate the effect of individual arcs and nodes on the description of feasibility in an uncapacitated network. This is done by developing an iterative algorithm for finding all (necessary) Gale-Hoffman inequalities for the network.
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  • 16
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    Annals of operations research 14 (1988), S. 245-289 
    ISSN: 1572-9338
    Keywords: 90C27 ; 68Q15 ; 68Q25 ; 68Rxx ; Parallel computer ; computational complexity ; polylog parallel algorithm ; P-completeness ; sorting ; shortest paths ; minimum spanning tree ; matching ; maximum flow ; linear programming ; knapsack ; scheduling ; traveling salesman ; dynamic programming ; branch and bound
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract This is a review of the literature on parallel computers and algorithms that is relevant for combinatorial optimization. We start by describing theoretical as well as realistic machine models for parallel computations. Next, we deal with the complexity theory for parallel computations and illustrate the resulting concepts by presenting a number of polylog parallel algorithms andP-completeness results. Finally, we discuss the use of parallelism in enumerative methods.
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    Annals of operations research 57 (1995), S. 233-249 
    ISSN: 1572-9338
    Keywords: Steiner tree ; game theory ; cost allocation ; integer programming ; linear programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract A cost allocation problem arising from the Steiner Tree (ST) problem in networks is analyzed. This cost allocation problem is formulated as a cost cooperative game in characteristic function form, referred to as theST-game. The class ofST games generalizes the class of minimum cost spanning tree games which were used in the literature to analyze a variety of cost allocation problems. In general, the core of anST-game may be empty. We construct an efficient Core Heuristic to compute a “good” lower bound on the maximum fraction of the total cost that can be distributed among users while satisfying the core constraints. Based on the Core Heuristic, we also provide a sufficient condition for a givenST not to be optimal for the linear programming relaxation of an integer programming formulation of theST problem. The Core Heuristic was implemented and tested on 76 data sets from the literature (Wong's, Aneja's and Beasley's Steiner tree problems). Core points were found for 69 of these cases, and points “close” to the core were computed in the others.
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  • 18
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    Annals of operations research 58 (1995), S. 67-98 
    ISSN: 1572-9338
    Keywords: Column generation ; convex programming ; cutting plane methods ; decomposition ; interior point method ; linear programming ; logarithmic barrier function ; nonsmooth optimization ; semi-infinite programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract The paper presents a logarithmic barrier cutting plane algorithm for convex (possibly non-smooth, semi-infinite) programming. Most cutting plane methods, like that of Kelley, and Cheney and Goldstein, solve a linear approximation (localization) of the problem and then generate an additional cut to remove the linear program's optimal point. Other methods, like the “central cutting” plane methods of Elzinga-Moore and Goffin-Vial, calculate a center of the linear approximation and then adjust the level of the objective, or separate the current center from the feasible set. In contrast to these existing techniques, we develop a method which does not solve the linear relaxations to optimality, but rather stays in the interior of the feasible set. The iterates follow the central path of a linear relaxation, until the current iterate either leaves the feasible set or is too close to the boundary. When this occurs, a new cut is generated and the algorithm iterates. We use the tools developed by den Hertog, Roos and Terlaky to analyze the effect of adding and deleting constraints in long-step logarithmic barrier methods for linear programming. Finally, implementation issues and computational results are presented. The test problems come from the class of numerically difficult convex geometric and semi-infinite programming problems.
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  • 19
    ISSN: 1572-9397
    Keywords: set partitioning ; preprocessing ; linear programming ; Lagrangian dual
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Given a finite ground set, a set of subsets, and costs on the subsets, the set partitioning problem is to find a minimum cost partition of the ground set. Many combinatorial optimization problems can be formulated as set partitioning problems. We present an approximation algorithm that produces high-quality solutions in an acceptable amount of computation time. The algorithm is iterative and combines problem size-reduction techniques, such as logical implications derived from feasibility and optimality conditions and reduced cost fixing, with a primal heuristic based on cost perturbations embedded in a Lagrangian dual framework, and cutting planes. Computational experiments illustrate the effectiveness of the approximation algorithm.
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    Order 14 (1997), S. 269-278 
    ISSN: 1572-9273
    Keywords: preemptive scheduling ; non preemptive scheduling ; linear programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The general non preemptive multiprocessor scheduling problem (NPMS) is NP-Complete, while in many specific cases, the same problem is Time-polynomial. A first connection between PMS and linear programming was established by Yannanakis, Sauer and Stone, who associated to any PMS instance some specific linear program. The main result inside this paper consists in a characterization of the partially ordered structures which allow the optimal values of any associated PMS instance to be equal to the optimal values of the corresponding linear programs.
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    Annals of operations research 73 (1997), S. 253-276 
    ISSN: 1572-9338
    Keywords: Data Envelopment Analysis ; game theory ; efficiency ; linear programming
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    Topics: Mathematics , Economics
    Notes: Abstract Dominant Competitive Factors, unique solutions to a new class of two-person ratio efficiency games, are introduced as a means for distinguishing exceptional aspects of individual performance. The vectors of input-output multipliers thus obtained may be analyzed collectively so that commonalities within groups and differences across groups may be discovered. The method is applied to "Program Follow-Through", the original impetus for developing Data Envelopment Analysis. Our results are compared with those of the earlier study, whereupon substantial new insights are obtained.
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    Annals of operations research 73 (1997), S. 299-321 
    ISSN: 1572-9338
    Keywords: Discriminant Analysis ; linear programming ; Data Envelopment Analysis ; insurance
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    Topics: Mathematics , Economics
    Notes: Abstract Data Envelopment Analysis (DEA) and Discriminant Analysis (DA) are similar in that both may be used to classify units as exhibiting either good or poor performance. Both use linear programming to select a set of factor weights that determines group membership relative to a "threshold" or hyperplane. This similarity was pointed out in an earlier paper, in which several methods which combine aspects of DA and DEA were suggested. This paper further develops one of these hybrid methods, which can be described as an efficiency approach to Discriminant Analysis. The various formulation options are considered with respect to their effects on solution quality and stability. The stability issue is raised by the fact that solution equivalence under data transformation (including both translation and rotation) is considered important in DA, and has significantly affected model formulation. Thus, the data transformation issue is studied for the hybrid method, and also for DEA. The hybrid method is applied to an insurance data set, where some firms are solvent and others in financial distress, to further evaluate the method and its possible formulations. DA methods are applied to the same data set to provide a basis for comparison. The hybrid method is shown to outperform the general discriminant models.
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    BIT 10 (1970), S. 95-105 
    ISSN: 1572-9125
    Keywords: Land-use planning ; accessibility ; uncertainty ; game theory ; linear programming
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    Topics: Mathematics
    Notes: Abstract One objective in regional planning is the creation of communities with great accessibility. Thus we should plan the locations of inhabitants and the activities of the region so that the total accessibility will be maximized subject to some restrictions. This is a quadratic programming problem, which can be solved by quadratic programming techniques, but we cannot then take into account the uncertainties of the problem. In this paper a new criterion function is proposed for accessibility, uncertainty problems in regional land-use planning. It is derived from Hurwicz's generalized maximin principle. Many advantages are gained, for the planning problem is separated into linear programming problems, the uncertainties are taken into consideration as in game theory and the methods of parametric programming are available. A simplified problem of the populations of three town areas is studied and the method is generalized for problems of many activities and areas.
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    Mathematical programming 40 (1988), S. 197-204 
    ISSN: 1436-4646
    Keywords: Greedy algorithms ; series parallel graphs ; linear programming
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    Topics: Computer Science , Mathematics
    Notes: Abstract This note describes some sufficient conditions for the maximum or minimum of a weighted flow (the weights are on paths, and are derived from weights on the edges of the path), of given volume in a series parallel graph to be found by a greedy algorithm.
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    Mathematical programming 35 (1986), S. 173-192 
    ISSN: 1436-4646
    Keywords: Computational complexity ; average running time ; simplex algorithm ; linear programming ; linear complementarity problem
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    Topics: Computer Science , Mathematics
    Notes: Abstract We show that a particular pivoting algorithm, which we call the lexicographic Lemke algorithm, takes an expected number of steps that is bounded by a quadratic inn, when applied to a random linear complementarity problem of dimensionn. We present two probabilistic models, both requiring some nondegeneracy and sign-invariance properties. The second distribution is concerned with linear complementarity problems that arise from linear programming. In this case we give bounds that are quadratic in the smaller of the two dimensions of the linear programming problem, and independent of the larger. Similar results have been obtained by Adler and Megiddo.
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    Mathematical programming 35 (1986), S. 193-224 
    ISSN: 1436-4646
    Keywords: Local improvement ; average performance of algorithms ; linear complementarity ; linear programming ; extremal set theory
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    Notes: Abstract We present a general abstract model of local improvement, applicable to such diverse cases as principal pivoting methods for the linear complementarity problem and hill climbing in artificial intelligence. The model accurately predicts the behavior of the algorithms, and allows for a variety of probabilistic assumptions that permit degeneracy. Simulation indicates an approximately linear average number of iterations under a variety of probability assumptions. We derive theoretical bounds of 2en logn and en 2 for different distributions, respectively, as well as polynomial bounds for a broad class of probability distributions. We conclude with a discussion of the applications of the model to LCP and linear programming.
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    Mathematical programming 40 (1988), S. 183-195 
    ISSN: 1436-4646
    Keywords: Karmarkar's method ; linear programming ; inexact projections
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    Notes: Abstract Variants of Karmarkar's algorithm are given for solving linear programs with unknown optimal objective valuez *. These new methods combine the approach of Goldfarb and Mehrotra for relaxing the requirement that certain projections be computed exactly with the approach of Todd and Burrell for generating an improving sequence of lower bounds forz * using dual feasible solutions. These methods retain the polynomial-time complexity of Karmarkar's algorithm.
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    Mathematical programming 42 (1988), S. 135-145 
    ISSN: 1436-4646
    Keywords: Degeneracy ; dual infeasibility ; linear programming ; primal degeneracy ; simplex algorithm
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    Topics: Computer Science , Mathematics
    Notes: Abstract The Revised Primal Simplex algorithm, in its simplest form, has no defence against degeneracy. Various forms of the perturbation method are usually effective, but most offer no guarantee of avoiding all degeneracy, and can lead to numerical difficulties. This paper presents a method that avoids cycling and circling by taking a dual approach. The degenerate subproblem consists of all the original variables, but only the degenerate transformed constraints. The current primal objective, which may be mixed, is used. This subproblem may be solved using the dual simplex algorithm, starting from the current dual infeasible solution, and with a zero dual objective. If the dual algorithm terminates optimally then the whole problem is optimal (subject to primal feasibility). Otherwise the final solution provides a non-basic direction which improves the value of the mixed primal objective and moves away from the degenerate vertex. A purification algorithm then renders the solution basic and further improves the mixed objective.
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    Mathematical programming 44 (1989), S. 27-41 
    ISSN: 1436-4646
    Keywords: Interior-point methods ; linear programming ; Karmarkar's algorithm ; polynomial-time algorithms ; logarithmic barrier function ; path following
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    Notes: Abstract We describe a primal-dual interior point algorithm for linear programming problems which requires a total of $$O\left( {\sqrt n L} \right)$$ number of iterations, whereL is the input size. Each iteration updates a penalty parameter and finds the Newton direction associated with the Karush-Kuhn-Tucker system of equations which characterizes a solution of the logarithmic barrier function problem. The algorithm is based on the path following idea.
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    Acta mathematicae applicatae sinica 12 (1996), S. 1-10 
    ISSN: 1618-3932
    Keywords: Neural network ; linear programming ; quadratic programming ; penalty function method
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    Topics: Mathematics
    Notes: Abstract Artificial neural network techniques have been introduced into the area of optimization in the recent decade. Some neural network models have been suggested to solve linear and quadratic programming problems. The Kennedy and Chua model[5] is one of these networks. In this paper results about the convergence of the model are obtained. Another related problem is how to choose a parameter value $$\tilde s$$ so that the equilibrium point of the network immediately and properly approximates the original solution. Such an estimation for the parameter is given in a closed form when the network is used to solve linear programming.
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    Numerical algorithms 19 (1998), S. 195-211 
    ISSN: 1572-9265
    Keywords: algorithms ; combinatorics ; linear programming ; Taylor series ; index ; assignment problem
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    Notes: Abstract We present a general method of solving differential-algebraic equations by expanding the solution as a Taylor series. It seems especially suitable for (piecewise) smooth problems of high index. We describe the method in general, discuss steps to be taken if the method, as initially applied, fails because it leads to a system of equations with identically singular Jacobian, and illustrate by solving two problems of index 5.
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    Designs, codes and cryptography 16 (1999), S. 271-289 
    ISSN: 1573-7586
    Keywords: Association scheme ; block design ; orthogonal array ; partially ordered set ; linear programming
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    Notes: Abstract A number of important families of association schemes—such as the Hamming and Johnson schemes—enjoy the property that, in each member of the family, Delsarte t-designs can be characterised combinatorially as designs in a certain partially ordered set attached to the scheme. In this paper, we extend this characterisation to designs in a product association scheme each of whose components admits a characterisation of the above type. As a consequence of our main result, we immediately obtain linear programming bounds for a wide variety of combinatorial objects as well as bounds on the size and degree of such designs analogous to Delsarte's bounds for t-designs in Q-polynomial association schemes.
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    Journal of optimization theory and applications 13 (1974), S. 484-489 
    ISSN: 1573-2878
    Keywords: Convex programming ; duality ; linear programming ; duality gaps
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    Topics: Mathematics
    Notes: Abstract For certain types of mathematical programming problems, a related dual problem can be constructed in which the objective value of the dual problem is equal to the objective function of the given problem. If these two problems do not have equal values, a duality gap is said to exist. No such gap exists for pairs of ordinary dual linear programming problems, but this is not the case for linear programming problems in which the nonnegativity conditionx ⩾ 0 is replaced by the condition thatx lies in a certain convex setK. Duffin (Ref. 1) has shown that, whenK is a cone and a certain interiority condition is fulfilled, there will be no duality gap. In this note, we show that no duality gap exists when the interiority condition is satisfied andK is an arbitrary closed convex set inR n .
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    Journal of optimization theory and applications 14 (1974), S. 305-318 
    ISSN: 1573-2878
    Keywords: Integer programming ; mathematical programming ; scheduling ; linear programming
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    Notes: Abstract The problem of scheduling orders at each facility of a large integrated steel mill is considered. Orders are received randomly, and delivery dates are established immediately. Each order is filled by converting raw materials into a finished saleable steel product by a fixed sequence of processes. The application of a deterministic mixed integer linear programming model to the order scheduling problem is given. One important criterion permitted by the model is to process the orders in a sequence which minimizes the total tardiness from promised delivery for all orders; alternative criteria are also possible. Most practical constraints which arise in steelmaking can be considered within the formulation. In particular, sequencing and resource availability constraints are handled easily. The order scheduling model given here contains many variables and constraints, resulting in computational difficulties. A decomposition algorithm is devised for solving the model. The algorithm is a special case of Benders partitioning. Computational experience is reported for a large-scale problem involving scheduling 102 orders through ten facilities over a six-week period. The exact solution to the large-scale problem is compared with schedules determined by several heuristic dispatching rules. The dispatching rules took into consideration such things as due date, processing time, and tardiness penalties. None of the dispatching rules found the optimal solution.
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    Journal of optimization theory and applications 46 (1985), S. 55-66 
    ISSN: 1573-2878
    Keywords: Optimal value function ; linear programming ; sensitivity analysis ; parametric programming ; multiple-objective linear programming
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    Notes: Abstract Often, the coefficients of a linear programming problem represent estimates of true values of data or are subject to systematic variations. In such cases, it is useful to perturb the original data and to either compute, estimate, or otherwise describe the values of the functionf which gives the optimal value of the linear program for each perturbation. If the right-hand derivative off at a chosen point exists and is calculated, then the values off in a neighborhood of that point can be estimated. However, if the optimal solution set of either the primal problem or the dual problem is unbounded, then this derivative may not exist. In this note, we show that, frequently, even if the primal problem or the dual problem has an unbounded optimal solution set, the nature of the values off at points near a given point can be investigated. To illustrate the potential utility of our results, their application to two types of problems is also explained.
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    Journal of optimization theory and applications 55 (1987), S. 1-21 
    ISSN: 1573-2878
    Keywords: Constrained nonsmooth convex programming ; penalty methods ; proximal methods ; linear programming
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    Topics: Mathematics
    Notes: Abstract An implementable algorithm for constrained nonsmooth convex programs is given. This algorithm combines exterior penalty methods with the proximal method. In the case of a linear program, the convergence is finite.
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    Journal of optimization theory and applications 93 (1997), S. 301-319 
    ISSN: 1573-2878
    Keywords: Convex sets ; polyhedral convex sets ; separation theorem ; Banach spaces ; duality theory ; weak topology ; linear programming
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    Topics: Mathematics
    Notes: Abstract The subject of this paper is to study the problem of the minimum distance to the complement of a convex set. Nirenberg has stated a duality theorem treating the minimum norm problem for a convex set. We state a duality result which presents some analogy with the Nirenberg theorem, and we apply this result to polyhedral convex sets. First, we assume that the polyhedral set is expressed as the intersection of some finite collection of m given half-spaces. We show that a global solution is determined by solving m convex programs. If the polyhedral set is expressed as the convex hull of a given finite set of extreme points, we show that a global minimum for a polyhedral norm is obtained by solving a finite number of linear programs.
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    Journal of combinatorial optimization 1 (1998), S. 413-426 
    ISSN: 1573-2886
    Keywords: scheduling ; preemptive scheduling ; release dates ; identical parallel machines ; average completion time ; approximation algorithms ; relaxations ; linear programming
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    Notes: Abstract We consider the problem of scheduling n jobs withrelease dates on m identical parallel machines to minimize the average completion time of the jobs. We prove that the ratio of the average completion time of the optimal nonpreemptive schedule to that of the optimal preemptive schedule is at most 7/3, improving a bound of $$(3 - \frac{1}{m})$$ Shmoys and Wein.
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    Journal of global optimization 12 (1998), S. 175-195 
    ISSN: 1573-2916
    Keywords: Multiple criteria ; linear programming ; disaggregation method ; ordinalregression analysis
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    Notes: Abstract A new model to assess customer satisfaction is developed through this paper. The proposed model is based on the principles of multicriteria analysis, using ordinal regression techniques. The procedure uses survey's data on customer satisfaction criteria and disaggregates simultaneously all the global satisfaction judgments via a linear programming disaggregation formulation. The model provides collective global and partial satisfaction functions as well as average satisfaction indices. These results sufficiently describe customer behavior and they can be used in the strategic planning of an organization. The implementation of the model in three real world applications is used for illustration and for testing the model's reliability. Finally, several extensions and future research in the area of customer satisfaction analysis are discussed.
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    Mathematical methods of operations research 42 (1995), S. 169-188 
    ISSN: 1432-5217
    Keywords: Multi-chain Markov Decision Processes ; average cost criterion ; state-action frequencies ; deviation measure ; linear programming ; lagrange formulation
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    Topics: Mathematics , Economics
    Notes: Abstract Linear Programming is known to be an important and useful tool for solving Markov Decision Processes (MDP). Its derivation relies on the Dynamic Programming approach, which also serves to solve MDP. However, for Markov Decision Processes with several constraints the only available methods are based on Linear Programs. The aim of this paper is to investigate some aspects of such Linear Programs, related to multi-chain MDPs. We first present a stochastic interpretation of the decision variables that appear in the Linear Programs available in the literature. We then show for the multi-constrained Markov Decision Process that the Linear Program suggested in [9] can be obtained from an equivalent unconstrained Lagrange formulation of the control problem. This shows the connection between the Linear Program approach and the Lagrange approach, that was previously used only for the case of a single constraint [3, 14, 15].
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    Mathematical methods of operations research 43 (1996), S. 161-167 
    ISSN: 1432-5217
    Keywords: Canonical order ; greedy algorithm ; linear programming
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    Topics: Mathematics , Economics
    Notes: Abstract Using the partial order technique, we describe a subclass of objective functions taking their optimum at the greedy point of a given feasible polyhedron inR n.
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    Mathematical methods of operations research 44 (1996), S. 171-187 
    ISSN: 1432-5217
    Keywords: Inverse problem ; spanning tree with partition constraint ; maximal flow ; linear programming ; dual problem
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    Topics: Mathematics , Economics
    Notes: Abstract In this paper we first discuss the properties of minimum spanning tree and minimum spanning tree with partition constraints. We then concentrate on the inverse problem of minimum spanning tree with partition constraints in which we need to adjust the weights of the edges in a network as less as possible so that a given spanning tree becomes the minimum one among all spanning trees that satisfy the partition restriction. Based on the calculation of maximum cost flow in networks, we propose a strongly polynomial algorithm for solving the problem.
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    Mathematical methods of operations research 46 (1997), S. 131-142 
    ISSN: 1432-5217
    Keywords: Ellipsoid method ; linear programming ; simplex ; volume
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    Topics: Mathematics , Economics
    Notes: Abstract Yamnitsky and Levin proposed a variant of Khachiyan's ellopsoid method for testing feasibility of systems of linear inequalities that also runs in polynomial time but uses simplices instead of ellipsoids. Starting with then-simplexS and the half-space {x¦a Tx ≤ β}, the algorithm finds a simplexS YL of small volume that enclosesS ∩ {x¦a Tx ≤ β}. We interpretS YL as a simplex obtainable by point-sliding and show that the smallest such simplex can be determined by minimizing a simple strictly convex function. We furthermore discuss some numerical results. The results suggest that the number of iterations used by our method may be considerably less than that of the standard ellipsoid method.
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    Mathematical methods of operations research 41 (1995), S. 71-88 
    ISSN: 1432-5217
    Keywords: Markov decision processes ; partially observable ; linear programming
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    Topics: Mathematics , Economics
    Notes: Abstract In this paper we use an approach which uses a superharmonic property of a sequence of functions generated by an algorithm to show that these functions converge in a non-increasing manner to the optimal value function for our problem, and bounds are given for the loss of optimality if the computational process is terminated at any iteration. The basic procedure is to add an additional linear term at each iteration, selected by solving a particular optimisation problem, for which primal and dual linear programming formulations are given.
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    Journal of optimization theory and applications 103 (1999), S. 521-542 
    ISSN: 1573-2878
    Keywords: Linear systems ; linear programming ; convexity ; polyhedra ; invariance
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    Notes: Abstract The problem of confining the trajectory of a linear discrete-time system in a given polyhedral domain is addressed through the concept of (A, B)-invariance. First, an explicit characterization of (A, B)-invariance of convex polyhedra is proposed. Such characterization amounts to necessary and sufficient conditions in the form of linear matrix relations and presents two major advantages compared to the ones found in the literature: it applies to any convex polyhedron and does not require the computation of vertices. Such advantages are felt particularly in the computation of the supremal (A, B)-invariant set included in a given polyhedron, for which a numerical method is proposed. The problem of computing a control law which forces the system trajectories to evolve inside an (A, B)-invariant polyhedron is treated as well. Finally, the (A, B)-invariance relations are generalized to persistently disturbed systems.
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    Journal of optimization theory and applications 84 (1995), S. 207-234 
    ISSN: 1573-2878
    Keywords: Pairwise comparisons ; eigenvectors ; analytic hierarchy process ; linear programming ; fuzzy sets ; membership values ; artificial intelligence
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    Topics: Mathematics
    Notes: Abstract One of the most difficult issues in many real-life decisionmaking problems is how to estimate the pertinent data. An approach which uses pairwise comparisons was proposed by Saaty and is widely accepted as an effective way of determining these data. Suppose that two matrices with pairwise comparisons are available. Furthermore, suppose that there is an overlapping of the elements compared in these two matrices. The problem examined in this paper is how to combine the comparisons of the two matrices in order to derive the priorities of the elements considered in both matrices. A simple approach and a linear programming approach are formulated and analyzed in solving this problem. Computational results suggest that the LP approach, under certain conditions, is an effective way for dealing with this problem. The proposed approach is of critical importance because it can also result in a reduction of the total required number of comparisons.
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    Journal of optimization theory and applications 85 (1995), S. 593-612 
    ISSN: 1573-2878
    Keywords: Proximal point methods ; convex programming ; quadratic programming ; linear programming
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    Notes: Abstract The proximal point method for convex optimization has been extended recently through the use of generalized distances (e.g., Bregman distances) instead of the Euclidean one. One advantage of these extensions is the possibility of eliminating certain constraints (mainly positivity) from the subproblems, transforming an inequality constrained problem into a sequence of unconstrained or equality constrained problems. We consider here methods obtained using a certain class of Bregman functions applied to convex quadratic (including linear) programming, which are of the interior-point type. We prove that the limit of the sequence generated by the method lies in the relative interior of the solution set, and furthermore is the closest optimal solution to the initial point, in the sense of the Bregman distance. These results do not hold for the standard proximal point method, i.e., when the square of the Euclidean norm is used as the Bregman distance.
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    Journal of optimization theory and applications 90 (1996), S. 357-380 
    ISSN: 1573-2878
    Keywords: Polyhedral sets ; extreme points ; multivalued maps ; continuity ; stability ; linear programming
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    Notes: Abstract This paper is focused on the stability properties of the extreme point set of a polyhedron. We consider a polyhedral setX(A,b) which is defined by a linear system of equality and inequality constraintsAx≤b, where the matrixA and the right-hand sideb are subject to perturbations. The extreme point setE(X(A,b)) of the polyhedronX(A,b) defines a multivalued map ℳ:(A,b)→E(X(A,b)). In the paper, characterization of continuity and Lipschitz continuity of the map ℳ is obtained. Boundedness of the setX(A,b) is not assumed It is shown that lower Lipschitz continuity is equivalent to the lower semicontinuity of the map ℳ and to the Robinson and Mangasarian-Fromovitz constraint qualifications. Upper Lipschitz continuity is proved to be equivalent to the upper semicontinuity of the map ℳ. It appears that the upper semicontinuity of the map ℳ implies the lower semicontinuity of this map. Some examples of using the conditions obtained are provided.
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    Journal of optimization theory and applications 93 (1997), S. 619-634 
    ISSN: 1573-2878
    Keywords: Quadratic penalty functions ; linear programming ; piece-wise-linear path-following algorithms ; characterization of optimal solutions ; finiteness
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    Notes: Abstract This paper takes a fresh look at the application of quadratic penalty functions to linear programming. Recently, Madsen et al. (Ref. 1) described a continuation algorithm for linear programming based on smoothing a dual l 1-formulation of a linear program with unit bounds. The present paper is prompted by the observation that this is equivalent to applying a quadratic penalty function to the dual of a linear program in standard canonical form, in the sense that both approaches generate continuous, piecewise-linear paths leading to the optimal solution set. These paths lead to new characterizations of optimal solutions in linear programming. An important product of this analysis is a finite penalty algorithm for linear programming closely related to the least-norm algorithm of Mangasarian (Ref. 2) and to the continuation algorithm of Madsen et al. (Ref. 1). The algorithm is implemented, and promising numerical results are given.
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    Journal of optimization theory and applications 100 (1999), S. 327-348 
    ISSN: 1573-2878
    Keywords: Convex programming ; semidefinite programming ; linear matrix inequalities ; linear programming ; constraint-aggregation method ; minimum-penalty path ; exterior path-following methods
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    Notes: Abstract A semidefinite programming problem is a mathematical program in which the objective function is linear in the unknowns and the constraint set is defined by a linear matrix inequality. This problem is nonlinear, nondifferentiable but convex. It covers several standard problems, such as linear and quadratic programming, and has many applications in engineering. In this paper, we introduce the notion of minimal-penalty path, which is defined as the collection of minimizers for a family of convex optimization problems, and propose two methods for solving the problem by following the minimal-penalty path from the exterior of the feasible set. Our first method, which is also a constraint-aggregation method, achieves the solution by solving a sequence of linear programs, but exhibits a zigzagging behavior around the minimal-penalty path. Our second method eliminates the above drawback by following efficiently the minimum-penalty path through the centering and ascending steps. The global convergence of the methods is proved and their performance is illustrated by means of an example.
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    Journal of optimization theory and applications 47 (1985), S. 349-368 
    ISSN: 1573-2878
    Keywords: Respiratory physiology ; underdetermined linear systems ; least squares ; linear programming
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    Topics: Mathematics
    Notes: Abstract In recent literature, grossly underdetermined linear models have been developed for certain experimental techniques in respiratory physiology. Because physiologically sensible solutions of the models are reasonably assumed to be smooth, it is possible to recover such solutions using smoothed least-squares techniques. Bounds on the variability of smooth solutions satisfying the model can be generated using linear programming.
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    Journal of optimization theory and applications 61 (1989), S. 487-491 
    ISSN: 1573-2878
    Keywords: Multicriteria optimization ; linear programming ; insoluble problems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This note concerns a method for analyzing insoluble multicriteria linear programming problems.
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    Journal of optimization theory and applications 62 (1989), S. 225-237 
    ISSN: 1573-2878
    Keywords: Redundancy ; degeneracy ; linear constraints ; linear programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper presents a degenerate extreme point strategy for active set algorithms which classify linear constraints as either redundant or necessary. The strategy makes use of an efficient method for classifying constraints active at degenerate extreme points. Numerical results indicate that significant savings in the computational effort required to classify the constraints can be achieved.
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    Journal of optimization theory and applications 63 (1989), S. 39-49 
    ISSN: 1573-2878
    Keywords: Inverse gravimetry problem ; linear programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract From the knowledge of the anomalies of the gravitational field, we reconstruct the mass density distribution in a large region of the state of Bahia (Brazil). This inverse gravimetry problem has been translated into a linear programming problem and solved using the simplex method. Both two-dimensional and three-dimensional models have been considered.
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    Journal of optimization theory and applications 54 (1987), S. 437-446 
    ISSN: 1573-2878
    Keywords: Parallel algorithms ; linear programming ; complementarity problem ; successive overrelaxation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A parallel successive overrelaxation (SOR) method is proposed for the solution of the fundamental symmetric linear complementarity problem. Convergence is established under a relaxation factor which approaches the classical value of 2 for a loosely coupled problem. The parallel SOR approach is then applied to solve the symmetric linear complementarity problem associated with the least norm solution of a linear program.
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    Journal of optimization theory and applications 91 (1996), S. 523-542 
    ISSN: 1573-2878
    Keywords: Duality theory ; shadow prices ; perturbations ; linear programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A systematic exposition of duality theory is given on what appears to be the optimal level of generality. A condition is offered which implies that the ideal of duality theory is achieved. For the case of linear programming, our approach leads to two novel features. In the first place, primal and dual LP-problems and complementarity conditions are defined canonically, without choosing a matrix form. In the second place, without deriving the explicit form of the dual problem, we show that the following well-known fact implies that the condition mentioned above holds: the polyhedral set property is invariant under linear maps. We give a new quick algorithmic proof of this fact.
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    Journal of optimization theory and applications 98 (1998), S. 83-108 
    ISSN: 1573-2878
    Keywords: Concave minimization ; reverse convex programs ; non-convex optimization ; global optimization ; test problems ; linear programming ; nonlinear programming ; computational experiments
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper presents a method for constructing test problems with known global solutions for concave minimization under linear constraints with an additional convex constraint and for reverse convex programs with an additional convex constraint. The importance of such a construction can be realized from the fact that the well known d.c. programming problem can be formulated in this form. Then, the method is further extended to generate test problems with more than one convex constraint, tight or untight at the global solution.
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    Journal of global optimization 9 (1996), S. 153-167 
    ISSN: 1573-2916
    Keywords: Reverse convex programs ; nonconvex optimization ; global optimization ; test problem generation ; linear programming ; nonlinear programming ; computational experiments
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper presents computational experience with a rather straight forward implementation of an edge search algorithm for obtaining the globally optimal solution for linear programs with an additional reverse convex constraint. The paper's purpose is to provide a collection of problems, with known optimal solutions, and performance information for an edge search implementation so that researchers may have some benchmarks with which to compare new methods for reverse convex programs or concave minimization problems. There appears to be nothing in the literature that provides computational experience with a basic edge search procedure. The edge search implementation uses a depth first strategy. As such, this paper's implementation of the edge search algorithm is a modification of Hillestad's algorithm [11]. A variety of test problems is generated by using a modification of the method of Sung and Rosen [20], as well as a new method that is presented in this paper. Test problems presented may be obtained at ftp://newton.ee.ucla.edu/nonconvex/pub/.
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