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A Study of Greedy, Local Search, and Ant Colony Optimization Approaches for Car Sequencing Problems

  • Jens Gottlieb
  • Markus Puchta
  • Christine Solnon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2611)

Abstract

This paper describes and compares several heuristic approaches for the car sequencing problem. We first study greedy heuristics, and show that dynamic ones clearly outperform their static counterparts. We then describe local search and ant colony optimization (ACO) approaches, that both integrate greedy heuristics, and experimentally compare them on benchmark instances. ACO yields the best solution quality for smaller time limits, and it is comparable to local search for larger limits. Our best algorithms proved one instance being feasible, for which it was formerly unknown whether it is satisfiable or not.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jens Gottlieb
    • 1
  • Markus Puchta
    • 1
  • Christine Solnon
    • 2
  1. 1.SAP AGWalldorfGermany
  2. 2.LIRIS, NautibusUniversity Lyon IVilleurbanne cedexFrance

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