Flexible flow shop scheduling problem with setup times and blocking constraint via genetic algorithm and simulation

Abstract

Abstract Flexible flow shop scheduling problem (FFSP) is recognized as an important class of problems in manufacturing systems. To consider more actual production factors, such as transportation time, setup times, blocking constraint, etc., we solved the FFSP using the improved genetic algorithm (GA) and discrete event simulation (DES). Firstly, a mathematical model for FFSP with the objective of minimizing total completion time was established. Besides, a GA mixed with Palmer heuristic algorithm was proposed to solve the mathematical model. Moreover, a DES software-plant simulation-was used to establish a more realistic production model, and an actual production workshop was modeled and optimized. After optimization, the total completion time and equipment utilization were greatly improved compared with the original scheduling. It shows the effectiveness and rationality of the proposed method to solve the actual FFSP.