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A Computational Study of Local Search Algorithms for Job Shop Scheduling

A Computational Study of Local Search Algorithms for Job Shop Scheduling We present a computational performance analysis of local search algorithms for job shop scheduling. The algorithms under Investigation are Iterative improvement, simulated annealing, threshold accepting, and genetic local search. Our study shows that simulated annealing performs best in the sense that it finds better solutions than the other algorithms within the same amount of running time. Compared to more tailored algorithms, simulated annealing still finds the best results but only under the assumption that running time is of no concern. Compared to tabu search, simulated annealing is outperformed especially with respect to running times.INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ORSA Journal on Computing INFORMS

A Computational Study of Local Search Algorithms for Job Shop Scheduling

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Publisher
INFORMS
Copyright
Copyright © INFORMS
Subject
Research Article
ISSN
0899-1499
DOI
10.1287/ijoc.6.2.118
Publisher site
See Article on Publisher Site

Abstract

We present a computational performance analysis of local search algorithms for job shop scheduling. The algorithms under Investigation are Iterative improvement, simulated annealing, threshold accepting, and genetic local search. Our study shows that simulated annealing performs best in the sense that it finds better solutions than the other algorithms within the same amount of running time. Compared to more tailored algorithms, simulated annealing still finds the best results but only under the assumption that running time is of no concern. Compared to tabu search, simulated annealing is outperformed especially with respect to running times.INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.

Journal

ORSA Journal on ComputingINFORMS

Published: May 1, 1994

Keywords: local search iterative improvement threshold accepting genetic algorithms simulated annealing job shop scheduling

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