摘要
为解决含有机器和工人双资源约束的柔性作业车间节能调度问题,在考虑交货期的基础上,建立了以总提前和拖期惩罚值及总能耗最小为目标的双资源柔性作业车间节能调度模型。提出了一种改进的非支配排序遗传算法(improved non-dominated sorting genetic algorithmⅡ,INSGA-Ⅱ)进行求解。针对所优化的目标,设计了一种三阶段解码方法以获得高质量的可行解;利用动态自适应交叉和变异算子以获得更多优良个体;改进拥挤距离以获得收敛性和分布性更优的种群。将INSGA-Ⅱ与多种多目标优化算法进行对比分析,实验结果表明所提算法可行且有效。
To handle the flexible job shop energy-saving scheduling with machines and workers constraints,on the considering of delivery time,the optimization model of dual resource constrained flexible job shop energy-saving scheduling is established with the goal of minimizing the total earliness and tardiness penalties,and total energy consumption.An improved non-dominated sorting genetic algorithm II(INSGA-II)is proposed.Aiming at the optimized objectives,a three-stage decoding method is designed to gain more feasible solutions.The dynamic adaptive crossover and mutation operators are applied to get more excellent individuals.The crowding distance is improved to obtain a population with better convergence and distribution.The result of comparing INSGA-II with several other multi-objective optimization algorithms,verifies the feasibility and effectiveness of the proposed algorithm.
作者
张洪亮
徐静茹
谈波
徐公杰
Zhang Hongliang;Xu Jingru;Tan Bo;Xu Gongjie(Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes(Anhui University of Technology),Ma'anshan 243032,China;School of Management Science and Engineering,Anhui University of Technology,Ma'anshan 243032,China;School of Intelligent Manufacturing Engineering,Ma'anshan University,Ma'anshan 243100,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2023年第4期734-746,共13页
Journal of System Simulation
基金
国家自然科学基金面上项目(71772002)
安徽普通高校重点实验室开放基金重点项目(CS2021-ZD01)
安徽省自然科学基金(2008085QG335)。
