关键词: 柔性车间调度, 粒子群算法, 一维粒子编码, 启发式规则

Abstract: In flexible job-shop scheduling with single piece and small batch production mode, the optimized objective is to reduce production costs, improve production efficiency and avoid bottleneck. This paper investigates an optimization model of Flexible Job-shop Scheduling Problems（FJSP）, which aims at a comprehensive objective combined with minimized makespan, machine total load and single maximum load. It designs a unidimensional-encoded Particle Swarm Optimization（PSO） taking probability as continuous particle component. Combined with completion-time-earliest heuristic rules, these components are discretized by probability interval to solve operation sequence scheduling and machine tools selecting. After comparing and analyzing different sizes of examples, the proposed algorithm is found a distinct advantage in solving large scale problems.

Key words: Flexible Job-shop Scheduling（FJS）, Particle Swarm Optimization（PSO）, unidimensional-encoded particle, heuristic rules