关键词: 柔性作业车间调度, 多目标优化, Pareto最优解, 粒子群算法, 小生境技术

Abstract: Aiming at the multi-objective optimization problem for flexible job-shop scheduling,an optimization method based on niching particle swarm optimization algorithm was proposed to obtain an optimum solution.A multi-objective optimization model that satisfied the constraints was constructed,and the segmented arrangement code was adopted to express the chromosomes.The PSO algorithm was used to obtain the external archive that stored some non-inferior solutions,which was updated based on particles'deletion probability to maintain the accuracy and diversity of the solutions.To select the best solution from the Pareto optimal solution set,an overall value estimation method was proposed.Through experimental verification,the method could solve multi-objective flexible job-shop scheduling problem effectively.

Key words: flexible job-shop scheduling, multi-objective optimization, Pareto optimum solution, particle swarm optimization, niche technology