Three meta-heuristics to solve the no-wait two-stage assembly flow shop scheduling problem

Authors

1 Payame Noor University, 19395-4697 Tehran, Iran

2 Department of Industrial Engineering, Amirkabir University of Technology,424 Hafez Avenue,Tehran,Iran

3 Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran ,Iran

4 Department of Industrial and Manufacturing Systems Engineering, University of Windsor, Windsor, Ontario, Canada

Abstract

This paper addresses the no-wait two-stage assembly flow shop scheduling problem (NWTSAFSP) with the objective of makespan minimization. The problem is a generalization of previously proposed general problem in the two-stage assembly flow shop scheduling problem (TSAFSP). The TSAFSP is NP-hard, thus the NWTSAFSP is NP-hard too and three meta-heuristic algorithms namely genetic algorithm (GA), differential evolution algorithm (DEA) and population-based variable neighborhood search (PVNS) are proposed in this article to solve this problem. Computational results reveal that PVNS outperforms other algorithms in terms of average error and average coefficient of variation (CV). Nevertheless, GA has the least run time among the proposed algorithms.

Keywords

Scientia Iranica
Volume 20, Issue 6 - Serial Number 14
Transactions on Industrial Engineering (E)
December 2013
Pages 2275-2283

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