Title: Optimisation of genetic algorithm parameters in flow shop scheduling using grey relational analysis

Authors: B. Shahul Hamid Khan, Kannan Govindan, R. Jeyapaul

Addresses: Department of Mechanical Engineering, Indian Institute of Information Technology Design and Manufacturing (IIITD&M), Kancheepuram, Indian Institute of Technology Madras Campus (IITM), Chennai 600 036, India. ' Department of Business and Economics, University of Southern Denmark, Campusvej 55, Odense-5230, Denmark. ' Department of Production Engineering, National Institute of Technology, Trichirappalli – 620 015, India

Abstract: This paper considers permutation flow shop scheduling problem with the objective of minimising the weighted sum of makespan and maximum tardiness, where the maximum tardiness is limited by a given upper bound value. This is NP hard problem in strong sense. A few attempts have been made to obtain good heuristic solutions to this problem. We have reviewed the related literature and propose a new hybrid genetic algorithm for the problem of considerations. A complete evaluation of the different parameters and operators of the algorithm using grey relational analysis in Taguchi method is also given. The evaluation of the hybrid algorithm is carried by 30 randomly generated small and large size problems with 900 instances. Computational experiments indicate that the proposed algorithm is much better than the existing ones.

Keywords: genetic algorithms; GAs; makespan; tardiness; multi-objective flow shops; flow shop scheduling; grey relational analysis; GRA; Taguchi methods.

DOI: 10.1504/IJAOM.2010.034584

International Journal of Advanced Operations Management, 2010 Vol.2 No.1/2, pp.25 - 45

Published online: 10 Aug 2010 *

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