A Hybrid Particle Swarm Optimization Approach for Scheduling Flow-Shops with Multiprocessor Tasks

Particle swarm optimization (PSO) technique is employed in many optimization and search problems due to its simplicity and ability to tackle these problems successfully. This paper shows application of PSO in scheduling hybrid flow-shops with multiprocessor tasks. This scheduling problem is often encountered in computing and industrial applications. In order to improve the performance of PSO, hybrid techniques were also employed. A comparative performance study is reported. It is observed that PSO and hybrid methods have merits in solving multiprocessor task scheduling in hybrid flow-shop environment.