Hybrid variable neighborhood search for multi objective flexible job shop scheduling problem

Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. Although the traditional optimization algorithms could obtain preferable results in solving the single objective FJSP. However, they are difficult to solve multi objective FJSP. A hybrid algorithm based on the particle swarm optimization (PSO) and variable neighborhood search (VNS) is proposed to solve the multi objective FJSP with several conflicting and incommensurable objectives. PSO has highly search ability for integrating local search and global search. Benchmark problems are used to evaluate and study the performance of the proposed algorithm. Computational results show that the proposed algorithm is efficient and effective approach.