基于混合的多目标遗传算法的多目标流水车间逆调度问题求解方法  

Multi-objective Genetic Algorithm for Solving Multi-objective Flow-shop Inverse Scheduling Problems

作　　者：牟健慧[1] 郭前建[1] 高亮[2] 张伟[1] 牟建彩 

机构地区：[1]山东理工大学机械工程学院,淄博255000 [2]华中科技大学数字制造装备与技术国家重点实验室,武汉430074 [3]广州华立科技职业学院,广州511325

出　　处：《机械工程学报》2016年第22期186-197,共12页Journal of Mechanical Engineering

基　　金：国家自然科学基金(51305244);山东省自然科学基金(ZR2013EEL015);山东省高等学校科技计划(J16LB04)资助项目

摘　　要：将逆优化理论与方法引入车间调度领域,探讨近年来车间调度领域出现的一种新方法"逆调度"。研究多目标流水车间逆调度问题,建立考虑调度效率和调度稳定性的数学模型,综合考虑了加工参数改变量、系统改变量以及完工时间和等目标。提出一种基于混合的多目标遗传算法(Hybrid multi-objective genetic algorithm,HMGA)的求解方法,将多种策略进行混合以提高算法性能,主要包括快速非支配排序遗传算法(Non-dominated sorting genetic algorithm II,NSGAII)中的快速非支配排序方法、两种多样性保持策略、混合的精英保留策略,以及改进的局部搜索策略等。通过实例测试与方差分析(Analysis of variance,ANOVA),验证了该算法的有效性。A new method of scheduling fields（Inverse scheduling problem,ISP） is discussed under the theories and methods of inverse optimization.The definition of an inverse scheduling problem is that the exact values of parameters（e.g.processing times,due dates） are controllable and a feasible job sequence is given but not optimal and pre-specified job sequence（s） become optimal through adjusting processing parameters for a target.The model of multi-objective ISP which considers scheduling efficiency and system stability is build.The adjustment of processing parameters,the changing of system and the weighted completion time are considered in this model.A hybrid multi-objective genetic algorithm is proposed to solve this problem.In order to improve the performance of algorithm,the multiple strategies are mixed,including rapid non-dominated sorting method,two kinds of diversity strategy,hybrid elitism strategy and efficient local search strategy.Finally,public problem instances and ANOVA analysis are provided for the proposed algorithm.The results demonstrate the effectiveness of the algorithm.

关 键 词：车间调度 逆调度 多目标进化算法 局部搜索算法 

分 类 号：TG156[金属学及工艺—热处理]