基于群体免疫算法的绿色车间调度研究  

Research on Green Job Shop Scheduling Based on Herd Immunity Optimizer

作　　者：马训德 毕利 王俊杰 Ma Xunde;Bi Li;Wang Junjie(School of Information Engineering,Ningxia University,Yinchuan 750021,China;Hefei Institutes of Physical Science,Chinese Academy of Sciences,Hefei 230031,China;University of Science and Technology of China,Hefei 230026,China)

机构地区：[1]宁夏大学信息工程学院,宁夏银川750021 [2]中国科学院合肥物质科学研究院,安徽合肥230031 [3]中国科学技术大学,安徽合肥230026

出　　处：《系统仿真学报》2024年第11期2578-2591,共14页Journal of System Simulation

基　　金：国家自然科学基金(62266034);宁夏自然科学基金重点项目(2023AAC02011)。

摘　　要：针对机器具有多转速的绿色柔性作业车间调度问题,以最大完工时间最小化和不同转速下的总能耗最小化为优化目标,构建了多转速下的绿色柔性车间调度模型,提出了一种离散的冠状病毒群体免疫算法(discrete coronavirus herd immunity optimizer,DCHIO)进行求解。针对多转速问题解空间较为庞大的特点,引入了离散化的个体更新方式,提出了一种多尺度联合搜索的种群更新机制以快速、均匀地搜索解空间;设计了动态变异操作以增强算法的种群多样性同时实现自适应调整;通过挖掘当前调度方案的经验知识,提出了基于知识驱动的邻域搜索策略,以同时减小最大完工时间和能源消耗。实验结果表明:所提算法可以有效解决多转速绿色柔性调度问题。In view of the green flexible job shop scheduling problem where machines have multiple speeds,a green flexible job shop scheduling model under multiple speeds was constructed to minimize the makespan and total energy consumption under different speeds.A discrete coronavirus herd immunity optimizer(DCHIO)was proposed for a solution.A discrete individual updating method was introduced for the relatively large solution space of the multi-speed problem,based on which a population updating mechanism with multi-scale joint search was proposed to search the solution space quickly and uniformly.A dynamic mutation operation was designed to enhance the population diversity of the algorithm while realizing the adaptive tuning.By mining the empirical knowledge of the current scheduling scheme,a knowledge-driven neighborhood search strategy was proposed to simultaneously reduce the makespan and energy consumption.The experimental results show that the algorithm proposed in this paper can effectively solve the green flexible scheduling problem under multiple speeds.

关 键 词：绿色调度 柔性作业车间 离散冠状病毒群体免疫算法 多转速机器 知识驱动邻域搜索 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]