A combined branch-and-bound and genetic algorithm based approach for a flowshop scheduling problem

A combined branch-and-bound and genetic algorithm based approach for a flowshop scheduling problem

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Article ID: iaor19971354
Country: Netherlands
Volume: 63
Issue: 1
Start Page Number: 397
End Page Number: 414
Publication Date: May 1996
Journal: Annals of Operations Research
Authors: , ,
Keywords: programming: branch and bound, heuristics
Abstract:

In this paper, the authors study the application of a meta-heuristic to a two-machine flowshop scheduling problem. The meta-heuristic uses a branch-and-bound procedure to generate some information, which in turn is used to guide a genetic algorithm’s search for optimal and near-optimal solutions. The criteria considered are makespan and average job flowtime. The problem has applications in flowshop environments where management is interested in reducing turn-around and job idle times simultaneously. The authors develop the combined branch-and-bound and genetic algorithm based procedure and two modified versions of it. Their performance is compared with that of three algorithms: pure branch- and-bound, pure genetic algorithm, and a heuristic. The results indicate that the combined approach and its modified versions are better than either of the pure strategies as well as the heuristic algorithm.

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