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Solving a Bi-Criteria Permutation Flow Shop Problem Using Immune Algorithm

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3 Author(s)
Reza Tavakkoli-Moghaddam ; Department of Industrial Engineering, University of Tehran, P.O. Box: 11365/4563, Tehran, Iran. e-mail: ; Ali-Reza Rahimi-Vahed ; Ali Hossein Mirzaei

A flow shop problem as a typical manufacturing challenge has gained wide attention in academic fields. In this paper, we consider a bi-criteria permutation flow shop scheduling problem, in which the weighted mean completion time and the weighted mean tardiness are to be minimized simultaneously. Since a flow shop scheduling problem has been proved to be NP-hard in strong sense, an effective multi-objective immune algorithm (MOIA) is proposed for searching locally Pareto-optimal frontier for the given problem. To prove the efficiency of the proposed algorithm, a number of test problems are solved and the efficiency of the proposed algorithm, based on some comparison metrics, is compared with a distinguished multi-objective genetic algorithm, i.e. SPEA-II. The computational results show that the proposed MOIA performs better than the above genetic algorithm, especially for large-sized problems

Published in:

2007 IEEE Symposium on Computational Intelligence in Scheduling

Date of Conference:

1-5 April 2007