A Hybrid Particle Swarm Optimization Algorithm with Diversity for Flow-Shop Scheduling Problem

This paper proposed a hybrid particle swarm optimization algorithm (Shadow hybrid PSO, SHPSO) to solve the flow-shop scheduling problem (FSSP). SHPSO adopts the idea of Kuoa´s HPSO model by not only combines the random-key (RK) encoding scheme, individual enhancement (IE) scheme, but also adds the diversification mechanism such as ARPSO model and competitive shadow particles to prevent premature convergence. Computation experiments results of Taillard´s seven representative instances of FSSP show that the SHPSO perform close to HPSO for FSSP to minimize makespan. Further recommendations and improved ideas will be discussed later in this paper.