A hybrid particle swarm optimization method for permutation flow shop scheduling problem

Abstract

The Permutation Flow Shop Scheduling Problem (PFSP) is a typical example in Production Scheduling, which has attracted many researchers’ attention. This paper takes to the advantage of the swarm characteristic of Particle Swarm optimization (PSO) algorithm to find the best particle in the solution space. The objective is to minimize the makespan. Firstly, the initial solution of the algorithm is generated by the famous heuristic NEH algorithm. The NEH algorithm was used to initialize the particle of global extreme values. Secondly, we take some optimized strategy to set the parameters, acceleration constant and nonlinear inertia weight strategy which based on random self-adaptively by means of chaos method for setting parameters. These optimized methods can avoid algorithm to be trapped in local optimum. At last, simulated results demonstrate that the hybrid PSO method is feasible and effective for the PFSP.