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Genetic Algorithm for the Permutation Flow-shop Scheduling Problem with Linear Models of Operations

Adam Janiak 1 Marie-Claude Portmann 1
1 MACSI - Industrial system modeling, analysis and operation
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
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). The purpose is to find a processing order of jobs (the same on each machine) and a resource allocation that minimize 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 employees some substantial problem properties which were proved. The results of some computational experiment are also included. || Le papier s'intéresse à un problème de "flow-shop" de permutation où les temps d'exécution des opération sur certaines machines sont des fonctions linéaires décroissantes de la quantité de ressources infiniment divisibles et consommables, quantité limitée
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Submitted on : Monday, September 25, 2006 - 5:02:23 PM
Last modification on : Tuesday, May 3, 2022 - 12:02:51 PM

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Adam Janiak, Marie-Claude Portmann. Genetic Algorithm for the Permutation Flow-shop Scheduling Problem with Linear Models of Operations. Annals of Operations Research, Springer Verlag, 1998, 83, pp.95-114. ⟨10.1023/A:1018924517216⟩. ⟨inria-00098505⟩

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