An effective hybrid particle swarm optimization algorithm for flexible job- shop scheduling problem

Flexible job-sop scheduling problem (FJSP) is based on the classical job-shop scheduling problem (JSP), however, it is even more harder than JSP because of the machine selection process in FJSP. In this paper, a particle swarm optimization (PSO) algorithm and a tabu search (TS) algorithm are integrated to solve the FJSP, the objective is to make the complete time minimum, i.e., to get the best makespan. In the new hybrid algorithm, PSO was used to produce enough high quality candidate solutions, and TS was used to find a near optimal solution around a given good solution. During the local search process, public critical blocks were found to make the local search space reduced deeply. The computational results have proved that the proposed hybrid algorithm is efficient and effective for solving FJSP, especially for the problems with large scale.