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Local search and suffix tree for car-sequencing problem with colors

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  • Gavranovic, Haris

Abstract

This paper describes an approximation solution method for the car sequencing problem with colors. Firstly, we study the optimality of problems with a single ratio constraint. This study also introduces a data structure for efficient calculation of the penalties related to ratio constraints. We describe the constructive greedy algorithm and variable neighborhood search adjusted for the problem with colors. Tabu metaheuristic is used to improve the results obtained by VNS. We then represent the cars with their constraints as letters over an alphabet and apply the algorithm to spell the motifs in order to improve the number of batch colors without decreasing the costs associated to the set of ratio constraints. The algorithm achieves 19 out of the 64 best results for instance sets A and B. These instances are the reference instances for Challenge ROADEF.

Suggested Citation

  • Gavranovic, Haris, 2008. "Local search and suffix tree for car-sequencing problem with colors," European Journal of Operational Research, Elsevier, vol. 191(3), pages 972-980, December.
  • Handle: RePEc:eee:ejores:v:191:y:2008:i:3:p:972-980
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    1. Smith, Kate & Palaniswami, M. & Krishnamoorthy, M., 1996. "Traditional heuristic versus Hopfield neural network approaches to a car sequencing problem," European Journal of Operational Research, Elsevier, vol. 93(2), pages 300-316, September.
    2. Gagne, Caroline & Gravel, Marc & Price, Wilson L., 2006. "Solving real car sequencing problems with ant colony optimization," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1427-1448, November.
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