TY - JOUR ID - 11744 TI - Meta-Heuristic Algorithms for Two-Stage Assembly Flow Shop Scheduling Problem with Considering Setup Times of Machines JO - Industrial Management Studies JA - JIMS LA - en SN - 2251-8029 AU - Yazdani, Mehdi AD - Assistant Professor, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch Y1 - 2020 PY - 2020 VL - 18 IS - 58 SP - 307 EP - 335 KW - Two-Stage Assembly Flow Shop Problem KW - Scheduling KW - Sequence- Independent Setup Times KW - Meta-Heuristic Algorithm DO - 10.22054/jims.2020.47551.2394 N2 - This paper deals with the problem of two-stage assembly flow shop scheduling with considering sequence-independent setup times .The objective is to minimize totalcompletion times of all orders. In this problem, there are several orders for one type of product. Each ordered product is formed of several different parts. At first, the parts are manufactured in a flow shop stage with some different machines and then they are assembled into a final product on a single machine. This paper presents three meta-heuristic algorithms, namely Parallel Variable Neighborhood Search (PVN) Artificial Immune Algorithm (AIA) and Simulated Annealing (SA), for solving under studied problem. The Taguchi experimental design method as an optimization technique is employed to tune different parameters and operators of presented algorithms. Also, Numerical experiments are used to evaluate the performance of the proposed algorithms. The results show that the PVNS algorithm performs better than the other algorithms UR - https://jims.atu.ac.ir/article_11744.html L1 - https://jims.atu.ac.ir/article_11744_d36baf6291c9fbceec5bd1f0a19ae30d.pdf ER -