Multi- resource flexible job shop scheduling problem based on hybrid genetic-particle swarm optimization algorithm

A multi-resource flexible job shop scheduling problem (MRFJSP) is proposed by adding transportation and assembly in the traditional flexible job shop scheduling problem (FJSP). A flexible job shop scheduling model including processing, transportation and assembly is established to minimize the completion time. In order to improve the searching ability of traditional genetic algorithm (GA) in job shop scheduling problem, a hybrid GA-PSO with optimization strategy is proposed, where single layer coding is used. The feasibility of the model is verified by an example, and the hybrid algorithm is compared with GA and PSO, which proves the superiority of the hybrid algorithm.