控制理论与应用2016，Vol.33Issue(10)：1281-1288,8.DOI:10.7641/CTA.2016.50666
面向多目标流水车间调度的多种群多目标遗传算法
Multipopulation multiobjective genetic algorithm for multiobjective permutation flow shop scheduling problem
摘要
Abstract
Since the permutation flow shop scheduling problem exits extensively in manufacturing enterprises, a mul-tiobjective flow shop scheduling problem with the objectives of minimizing the makespan and the total tardiness is inves-tigated in this paper. In order to solve it, a multipopulation multiobjective genetic algorithm based on decomposition is proposed. The proposed algorithm decomposes the investigated problem into multiple single objective subproblems intro-duced into the iteration course step by step. At each iteration, multiple subpopulations are constructed for the current solved subproblems based on the distribution of population, which realizes the goal of solving them simultaneously. The evolution of multiple subpopulations can be used to search the optimal solutions of multiple subproblems. Experimental results on some instances show that the proposed algorithm can get better performance in solving the multiobjective permutation flow shop scheduling problem.关键词
多种群/遗传算法/多目标优化/流水车间调度Key words
multipopulation/genetic algorithm/multiobjective optimization/flow shop scheduling分类
信息技术与安全科学引用本文复制引用
付亚平,黄敏,王洪峰,王兴伟..面向多目标流水车间调度的多种群多目标遗传算法[J].控制理论与应用,2016,33(10):1281-1288,8.基金项目
国家杰出青年科学基金项目(71325002,61225012),国家自然科学基金项目(71671032,61673228),流程工业综合自动化国家重点实验室基础科研业务费(2013ZCX11) （71325002,61225012）
