Parallel Taboo Search Techniques for the Job Shop Scheduling Problem
We apply the global optimization technique called taboo search to the job shop scheduling problem and show that our method is typically more efficient than the shifting bottleneck procedure, and also more efficient than a recently proposed simulated annealing implementation. We also identify a type...
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Veröffentlicht in: | INFORMS journal on computing 1994-05, Vol.6 (2), p.108-117 |
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container_title | INFORMS journal on computing |
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creator | Taillard, Eric D |
description | We apply the global optimization technique called taboo search to the job shop scheduling problem and show that our method is typically more efficient than the shifting bottleneck procedure, and also more efficient than a recently proposed simulated annealing implementation. We also identify a type of problem for which taboo search provides an optimal solution in a polynomial mean time in practice, while an implementation of the shifting bottleneck procedure seems to take an exponential amount of computation time. Included are computational results that establish new best solutions for a number of benchmark problems from the literature. Finally, we give a fast parallel algorithm that provides good solutions to very large problems in a very short computation time.
INFORMS Journal on Computing , ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499. |
doi_str_mv | 10.1287/ijoc.6.2.108 |
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subjects | complexity parallel algorithms scheduling taboo search technique |
title | Parallel Taboo Search Techniques for the Job Shop Scheduling Problem |
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