Lot Streaming in No-wait Multi Product Flowshop Considering Sequence Dependent Setup Times and Position Based Learning Factors

In this paper, a flowshop scheduling problem is studied. The importance of this study is that it considers different constraints simultaneously. These constraints are Lot Streaming, Position based learning factors, sequence dependent setup times and the fact that the flowshop line is no-wait. Lot streaming divide the lots of products into portions called sublots in order to reduce the lead times and work-in-process, and increase the machine utilization rates. The objective is to minimize the makespan. To clarify the system, mathematical model of the problemis presented. Since the problemis strongly NP-hard, two hybrid metaheuristics algorithms are proposed to solve the problem. These algorithms are based on the Variable Neighborhood Search (VNS), which is proved as an effective method for combinatorial optimization problems. In the proposed VNS, an efficient scheme for neighborhood search based on Tabu Search (TS) and Simulated Annealing (SA) is presented to strengthen the local searches. At the last part, computation results are provided to evaluate the efficiency of VNSSA and VNSTS. In order to verify the effectiveness of proposed algorithms, Relative percentage Deviation along with statistical analysis is presented.The computational results show that VNSSA outperforms VNSTS in most instances.