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Genetic algorithm for the permutation flow-shopscheduling problem with linear models of operations

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  • Adam Janiak
  • Marie-Claude Portmann

Abstract

The paper deals with a permutation flow-shop problem where processing times of jobs on some machines are linear, decreasing functions with respect to the amount of continuously-divisible, non-renewable, locally and totally constrained resources, e.g. energy, catalyzer, raw materials, etc. The purpose is to find a processing order of jobs that is the same on each machine and a resource allocation that minimizes the length of the time required to complete all jobs, i.e. makespan. Since the problem is strongly NP-hard, some heuristic algorithms of a genetic type were applied to solve it. These algorithms strongly employ some substantial problem properties, which were proved. The results of some computational experiments are also included. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • Adam Janiak & Marie-Claude Portmann, 1998. "Genetic algorithm for the permutation flow-shopscheduling problem with linear models of operations," Annals of Operations Research, Springer, vol. 83(0), pages 95-114, October.
    • Handle: RePEc:spr:annopr:v:83:y:1998:i:0:p:95-114:10.1023/a:1018924517216
    DOI: 10.1023/A:1018924517216
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    Cited by:

    1. Yaron Leyvand & Dvir Shabtay & George Steiner & Liron Yedidsion, 2010. "Just-in-time scheduling with controllable processing times on parallel machines," Journal of Combinatorial Optimization, Springer, vol. 19(3), pages 347-368, April.
    2. Néron, Emmanuel & Baptiste, Philippe & Gupta, Jatinder N. D., 2001. "Solving hybrid flow shop problem using energetic reasoning and global operations," Omega, Elsevier, vol. 29(6), pages 501-511, December.

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