摘要
针对柔性作业车间的调度优化问题,以最小化完工时间,最小化设备总负荷和最小化车间总能耗为目标建立多目标调度模型,提出一种改进NSGA-Ⅲ算法。在算法的初始阶段采取4种不同编码方式共同生成初始化种群,保证种群分布均匀的同时,缩小搜索的解空间大小;基于拥挤度的父代个体选择方式,使具有更优基因个体参与到进化当中。引入部分解的邻域搜索策略,解决NSGA-Ⅲ全局搜索时局部搜索较弱的问题。利用10组BRdate标准算例对改进NSGA-Ⅲ算法和原始NSGA-Ⅲ算法进行对比测试,改进NSGA-Ⅲ算法搜索到的非支配解数量占76%,远高于NSGA-Ⅲ算法所占的24%,验证了所提出算法的有效性和可靠性。
Aiming at the scheduling optimization problem of the flexible job shop,a multi-objective scheduling model is established with the goal of minimizing the completion time,minimizing the total load of the equipment and minimizing the total energy consumption in workshop and an improved NSGA-Ⅲalgorithm is proposed.4 different encoding methods are adopted in the initial stage of the algorithm to generate the initial population,which ensures the uniformity of the population distribution.The selection method of parent individuals based on crowding degree enables individuals with better genes to participate in evolution.The neighborhood search strategy of partial solution is adopted to solve the problem of weak local search in NSGA-Ⅲglobal search.Finally,10 BRdate standard examples were used to compare and test the improved NSGA-Ⅲalgorithm and the original NSGA-Ⅲalgorithm.The number of non-dominated solutions searched by the improved NSGA-Ⅲalgorithm accounted for 76%,which was much higher than that of the NSGA-Ⅲalgorithm 24%,verifying the effectiveness and reliability of the proposed algorithm.
作者
孙浩
刘环宇
赵柏栋
张玉嘉
杨振
王德权
SUN Hao;LIU Huan-yu;ZHAO Bai-dong;ZHANG Yu-jia;YANG Zhen;WANG De-quan(School of Mechanical Engineering and Automation,Dalian Polytechnic University,Dalian 116034,China)
出处
《组合机床与自动化加工技术》
北大核心
2022年第7期165-168,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
辽宁省教育厅科学研究项目(J2020108)
本科教育教学总和改革项目(JGLX2021032)。
关键词
柔性车间调度
NSGA-Ⅲ
多种群
邻域搜索策略
flexible shop scheduling
NSGA-Ⅲ
multi-population
neighborhood search strategy
