A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation

A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation

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Article ID: iaor20052538
Country: Netherlands
Volume: 159
Issue: 3
Start Page Number: 651
End Page Number: 662
Publication Date: Dec 2004
Journal: European Journal of Operational Research
Authors: ,
Keywords: heuristics
Abstract:

We propose in this paper an effective heuristic algorithm to solve a scheduling problem that comes from industry. The workshop is an hybrid flow shop with recirculation and the problem is to perform jobs between a release date and a due date, in order to minimize the weighted number of tardy jobs. Firstly, an integer linear programming formulation of the problem is proposed, then a lower bound, a greedy algorithm and a genetic algorithm are described as approximate methods. To evaluate these heuristics, experiences on instances like industrial ones are computed, and show the efficiency of the genetic algorithm.

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