Performance of Particle Swarm Optimization in Scheduling Hybrid Flow-Shops with Multiprocessor Tasks

In many industrial and computing applications, proper scheduling of tasks can determine the overall efficiency of the system. The algorithm, presented in this paper, tackles the scheduling problem in a multi-layer multiprocessor environment, which exists in many computing and industrial applications. Based on the scheduling terminology, the problem can be defined as multiprocessor task scheduling in hybrid flow-shops. This paper presents a particle swarm optimization algorithm for the solution and reports its performance. The results are compared with other well known meta-heuristic techniques proposed for the solution of the same problem. Our results show that particle swarm optimization has merits in solving multiprocessor task scheduling in a hybrid flow-shop environment.