Payame Noor University, 19395-4697 Tehran, Iran
Department of Industrial Engineering, Amirkabir University of Technology,424 Hafez Avenue,Tehran,Iran
Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran ,Iran
Department of Industrial and Manufacturing Systems Engineering, University of Windsor, Windsor, Ontario, Canada
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.