A hybrid algorithm for flexible job shop scheduling problem with an assembly stage and sequence dependent setup time

A flexible job shop scheduling problem with assembly operations and sequence dependent setup time is studied in this paper. In this problem, at the first stage, the parts are processed in a flexible job shop system and then they are assembled in an assembly stage to produce products. Setup time is needed when a machine starts processing the parts or it changes items. At first, a linear model is introduced to express the problem. The objective is to minimize the completion time of all products. Then since the problem is NP-hard, a hybrid metaheuristic algorithm is presented. The proposed algorithm is called a Hybrid Particle Swarm Optimization with a Parallel Variable Neighborhood Search algorithm (HPSOPVNS). Finally, the numerical experiments are used to evaluate and validate the performance of the mathematical model and proposed algorithm. The computational results show that hybrid algorithm achieves better performance than Particle Swarm Optimization algorithm (PSO).

Keywords:

Flexible job shop scheduling , Assembly , Setup time , Particle swarm optimization , Parallel variable neighborhood search