A Hybrid Particle Swarm Optimization Algorithm for Flow Shop Group Scheduling Problem with Sequence Dependent Setup Time

A particle swarm optimization (PSO) algorithm for flow shop sequence dependent group scheduling (FSDGS) problem with minimization of makespan criterion (Fm| fm, Sijk, prmu| Cmax ) is proposed in this research. An encoding scheme based on ranked order value (ROV) is developed which converts the continuous position value of particles in PSO to job permutation and group permutation. A neighborhood search strategy called individual enhancement (IE) is fused to enhance the search and to balance the exploration and exploitation. The performance of the algorithm is compared with the available algorithms in literature based on available test problems. The results show that the proposed algorithm has a superior performance compared to the available ones in literature.