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

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), Dierential 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 Coecient of Variation (CV). Nevertheless, GA has the least run time among the proposed algorithms.