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  • 2000-2004
  • 1995-1999  (2)
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  • 1997  (2)
  • ddc:000  (2)
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  • 2000-2004
  • 1995-1999  (2)
  • 1990-1994
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  • 1
    Publication Date: 2014-11-02
    Description: In this paper, we present a Dantzig-Wolfe decomposition for the $NP$-hard multiple-depot vehicle scheduling problem in public mass transit. It turned out that such a decomposition approach is an unsuitable method to solve such kind of multicommodity flow problems. The major obstacle to solve such problems is that the continuous master problem relaxations become too hard to be solved efficiently. Especially for problems with more than one thousand timetabled trips, the LU factorization in solving a restricted master problem takes far too much time. We will describe our computational experiments in detail and discuss the reasons why the decomposition method fails in this case. Our computational investigations are based on real-world problems from the city of Hamburg with up to 2,283 timetabled trips. Our decomposition implementation is compared with a delayed column generation to solve the linear programming (LP) relaxation directly. This LP method can solve the LP relaxations of the integer linear programming formulation exactly for truly large-scale real-world problems of the cities of Berlin and Hamburg.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/postscript
    Format: application/pdf
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  • 2
    Publication Date: 2020-08-05
    Description: This paper presents an integer linear programming approach with delayed column generation for the {\em NP} Multiple-Depot Vehicle Scheduling Problem (MDVSP) in public mass transit. We describe in detail all basic ingredients of our approach that are indispensable to solve truly large-scale real-world instances to optimality, and we report on computational investigations that are based on real-world instances from the city of Berlin, the city of Hamburg, and the region around Hamburg. These real-world instances have up to 25 thousand timetabled trips and 70 million dead-head trips. Computational tests using the data of the Hamburger Hochbahn AG indicate savings of several vehicles and a cost reduction of about 10\% compared with the solution provided by HOT II, the vehicle scheduling tool of the HanseCom GmbH, Hamburg. Parts of our algorithms are already integrated in the BERTA system of the Berliner Verkehrsbetriebe (BVG) and will soon be integrated in the MICROBUS system of the Gesellschaft für Informatik, Verkehrs- und Umweltplanung mbH (IVU), Berlin.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/postscript
    Format: application/postscript
    Format: application/pdf
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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