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  • 1995-1999  (9)
  • 1998  (4)
  • 1996  (5)
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  • 1995-1999  (9)
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  • 1
    Title: Optimal vehicle scheduling in public transit. Zugl.:Berlin, Technische Universität, Diss. 1997
    Author: Löbel, Andreas
    Publisher: Aachen :Shaker,
    Year of publication: 1998
    Pages: 172 S.
    Series Statement: Berichte aus der Mathematik
    Type of Medium: Book
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  • 2
    Title: Lagrangean Relaxations and Subgradient Methods for Multiple-Depot Vehicle Scheduling Problems /; Preprint SC 96-22
    Author: Kokott, Andreas
    Contributer: Löbel, Andreas
    Publisher: Berlin :Konrad-Zuse-Zentrum für Informationstechnik,
    Year of publication: 1996
    Pages: 24 S.
    Series Statement: Preprint / Konrad-Zuse-Zentrum für Informationstechnik Berlin Preprint SC 96-22
    ISSN: 0933-7911
    Type of Medium: Book
    Language: English
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  • 3
    Publication Date: 2014-02-26
    Description: This paper addresses the problem of scheduling vehicles in a public mass transportation system. We show how this problem can be modelled as a special multicommodity flow problem and outline the solution methodology we have developed. Based on polyhedral investigations, we have designed and implemented a branch&cut algorithm and various heuristics with which real vehicle scheduling problems of truely large scale can be solved to optimality. We describe some implementation issues and report computational results.
    Keywords: ddc:000
    Language: German
    Type: reportzib , doc-type:preprint
    Format: application/postscript
    Format: application/pdf
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  • 4
    Publication Date: 2014-11-02
    Description: This paper presents a large-scale real-world application of the minimum-cost flow problem, describes some details of a new implementation of the network simplex algorithm, and reports on computational comparisions. The real-world test sets include minimum-cost flow problems that are based on single-depot vehicle scheduling problems and on a Lagrangean relaxation of multiple-depot vehicle scheduling problems. Some of the problems are extremely large with up to 42,000 nodes and 20,000,000 arcs. The standard test problems are generated with NETGEN and include parts of the DIMACS standard problems. Our network simplex code is compared with \mbox{RELAX-IV}, Cost Scaling 2 version 3.4, and CPLEX's network solver NETOPT.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/postscript
    Format: application/pdf
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  • 5
    Publication Date: 2020-03-09
    Description: Dieser Artikel behandelt einen Ansatz zur zielorientierten Optimierung der Dienstplanung im ÖPNV. Der Ansatz zielt auf die vollständige Ausnutzung aller planerischen Freiheitsgrade unter korrekter Berücksichtigung von gesetzlichen, tariflichen, technischen und betrieblichen Rahmenbedingungen. Er basiert auf mathematischen Optimierungstechniken, die wir gegenwärtig in einem vom Bundesministerium für Bildung und Forschung ({\tt bmb+f}) geförderten Verbundprojekt in einer Kooperation zwischen der HanseCom GmbH, der IVU GmbH und dem Konrad-Zuse-Zentrum für Informationstechnik Berlin entwickeln. Es ist geplant, das Verfahren in die Softwareprodukte HOT II, MICROBUS II und OPUS zu integrieren. Verhandlungen mit den Berliner Verkehrsbetrieben über eine Projektbeteiligung und Integration unserer Software in BERTA sind zur Zeit im Gang. Wir beschreiben die Methodik des Ansatzes, diskutieren Aspekte seiner praktischen Verwendung, und wir berichten über den Stand der Entwicklung.
    Keywords: ddc:000
    Language: German
    Type: reportzib , doc-type:preprint
    Format: text/plain
    Format: application/pdf
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  • 6
    Publication Date: 2020-08-05
    Language: English
    Type: bookpart , doc-type:bookPart
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  • 7
    Publication Date: 2014-11-02
    Description: This paper presents two Lagrangean relaxation approaches for the {\em NP}-hard multiple-depot vehicle scheduling problem in public mass transit and reports on computational investigations. Our Lagrangean relaxation approaches can be applied to generate very tight lower bounds and to compute feasible solutions efficiently. A further application is to use the Lagrangean relaxations as new pricing strategies for a delayed column generation of a branch-and-cut approach. The computational investigations are based on real-world test sets from the cities of Berlin and Hamburg having up to 25 thousand timetabled trips and 70 million dead-head trips.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/postscript
    Format: application/pdf
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  • 8
    Publication Date: 2014-11-02
    Description: This paper investigates the solution of the linear programming (LP) relaxation of the multicommodity flow formulation of the multiple-depot vehicle scheduling problems arising in public mass transit. We develop a column generation technique that makes it possible to solve the huge linear programs that come up there. The technique, which we call {\em Lagrangean pricing}, is based on two different Lagrangean relaxations. We describe in detail the basic ingredients of our approach and give computational results for large-scale test data (with up to 70 million variables) from three German public transportation companies. Because of these results, we propose Lagrangean pricing as one of the basic ingredients of an effective method to solve multiple-depot vehicle scheduling problems to proven optimality.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Format: application/postscript
    Format: application/postscript
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  • 9
    Publication Date: 2020-03-09
    Description: The world has experienced two hundred years of unprecedented advances in vehicle technology, transport system development, and traffic network extension. Technical progress continues but seems to have reached some limits. Congestion, pollution, and increasing costs have created, in some parts of the world, a climate of hostility against transportation technology. Mobility, however, is still increasing. What can be done? There is no panacea. Interdisciplinary cooperation is necessary, and we are going to argue in this paper that {\em Mathematics\/} can contribute significantly to the solution of some of the problems. We propose to employ methods developed in the {\em Theory of Optimization\/} to make better use of resources and existing technology. One way of optimization is better planning. We will point out that {\em Discrete Mathematics\/} provides a suitable framework for planning decisions within transportation systems. The mathematical approach leads to a better understanding of problems. Precise and quantitative models, and advanced mathematical tools allow for provable and reproducible conclusions. Modern computing equipment is suited to put such methods into practice. At present, mathematical methods contribute, in particular, to the solution of various problems of {\em operational planning}. We report about encouraging {\em results\/} achieved so far.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/postscript
    Format: application/pdf
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