改进松鼠搜索算法求解分布式节能柔性调度  

Improved squirrel search algorithm to solve distributed energy-efficient flexible scheduling

作　　者：曾亮 石俊洋 王珊珊 李维刚[3] Zeng Liang;Shi Junyang;Wang Shanshan;Li Weigang(School of Electrical&Electronic Engineering,Hubei University of Technology,Wuhan 430068,China;Hubei Key Laboratory for High-efficiency Utilization of Solar Energy&Operation Control of Energy Storage System,Wuhan 430068,China;School of Information Science&Engineering,Wuhan University of Science&Technology,Wuhan 430081,China)

机构地区：[1]湖北工业大学电气与电子工程学院,武汉430068 [2]太阳能高效利用及储能运行控制湖北省重点实验室,武汉430068 [3]武汉科技大学信息科学与工程学院,武汉430081

出　　处：《计算机应用研究》2024年第3期848-853,共6页Application Research of Computers

基　　金：国家重点研发计划资助项目(2018YFC0116100);湖北省重点研发计划资助项目(2020BAB114);湖北省教育厅科学研究计划重点资助项目(D20211402)。

摘　　要：为了优化同时考虑最大完工时间和机器能耗的双目标分布式柔性作业车间调度问题,提出了一种改进的多目标松鼠搜索算法。引入了基于升序排列规则的转换机制,实现了松鼠位置向量与调度解之间的转换,并针对机器空闲时间设计了从半主动到主动的解码策略。针对不同优化目标设计了三种种群初始化策略。同时提出了动态捕食者策略来更好地协调算法的全局探索和局部开发能力。设计了四种领域搜索策略用于增加种群多样。20个实例上的实验结果验证了改进后的算法求得解的质量和多样性更好,从而证明了其可有效求解分布式节能柔性调度问题。To optimize the distributed flexible Job-Shop scheduling problem considering both the makespan and machine energy consumption,this paper proposed an improved multi-objective squirrel search algorithm.The algorithm introduced a conversion mechanism based on ranked order value to achieve the conversion between squirrel position vectors and scheduling solutions,and designed decoding strategy from semi-active to active for machine idle time.Additionally,it devised three population initialization strategies based on different optimization objectives.The proposed dynamic predator strategy could better coordinate the algorithm’s global exploration and local exploitation capabilities.Finally,the algorithm used four local searches to increase population diversity.Experimental results on 20 instances show that the improved algorithm achieves better quality and diversity of solutions,proving that it can effectively solve the distributed energy-efficient flexible scheduling problem.

关 键 词：松鼠搜索算法 分布式柔性车间调度 节能调度 多目标优化 优化算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TH165[自动化与计算机技术—控制科学与工程]