Fuzzy Particle Swarm Optimization Algorithm for Manufacturing Resource Scheduling

Abstract

In this paper, the problem of scheduling production resources in an intelligent manufacturing system is considered. The problem is defined as a multi-criteria optimization problem that requires optimization of multiple objectives such as total processing time, maximum utilization of machine tools and minimum material transport flows. In order to effectively solve this optimization problem, the paper presents the multi-criteria optimization PSO algorithm improved using fuzzy logic, FPSO (Fuzzy Particle Swarm Optimization). The inertial coefficients of the algorithm are adaptively adjusted by applying fuzzy logic, in order to balance local and global search capabilities. Experimental results obtained by the proposed fuzzy particle swarm algorithm and their comparison with published results obtained by generic (gPSO) and chaotic (cPSO) algorithms suggest the effectiveness of the proposed FPSO algorithm in solving production resource planning problems.