A genetic search algorithm to optimize job sequencing under technological constraint in a rolling-mill facility

A genetic search algorithm to optimize job sequencing under technological constraint in a rolling-mill facility

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Article ID: iaor19961664
Country: Germany
Volume: 17
Issue: 2/3
Start Page Number: 183
End Page Number: 191
Publication Date: Apr 1995
Journal: OR Spektrum
Authors: ,
Keywords: heuristics
Abstract:

This article presents some results from the application of a genetic search algorithm to solve a job scheduling problem where setup costs depend on the order of the jobs. An empirical study shows that, for small problems, the solutions given by the genetic algorithm are as good as those obtained with a mixed-integer linear program. For larger problems that are computationally infeasible, the authors benchmark the genetic solutions against traditional scheduling heuristics. They also study different population management strategies that can improve the performance of the algorithm. Finally, future research avenues are discussed.

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