摘要
基于分布式柔性作业车间问题特点,构建了以最小化最大完工时间、工厂总能耗和设备总负载为目标函数的数学模型,并对3个目标函数采用线性加权和法进行归一化。在传统的海鸥优化算法基础上,改进了自适应附加变量更新策略,提高算法后期的局部寻优能力和收敛精度。融合麻雀算法中的飞行机制,扩大个体局部寻优范围,进一步提高寻优精度。引入针对关键工厂的变邻域搜索算法,拓展了邻域搜索范围,增强了算法的局部搜索能力。通过标准算例和工厂实际算例的验证,证明了改进海鸥优化算法(Improve Seagull Optimization Algorithm,ISOA)在求解多目标分布式柔性作业车间问题上的有效性和可行性。
Based on the characteristics of distributed flexible job-shop problems,a mathematical model was constructed with the objective functions of minimizing completion time,factory energy consumption,and equipment load,and the three objectives were normalized using linear weighted sum method.On the basis of the traditional Seagull Optimization Algorithm(SOA),an adaptive additional variable update strategy has been improved to improve the local optimization ability and convergence accuracy of the algorithm in the later stage.The flight mechanism in the sparrow algorithm was integrated to expand the local optimization range of individuals,and further improve the optimization accuracy.Introducing a variable neighborhood search algorithm for key factories has expanded the neighborhood search range and enhanced the local search ability of the Seagull algorithm.The effectiveness and feasibility of ISOA in solving multi-objective distributed and flexible job-shop problems were verified through standard and actual factory examples.
作者
孙鸿羽
吉卫喜
李威
刘凯
SUN Hongyu;JI Weixi;LI Wei;LIU Kai(School of Mechanical Engineering,Jiangnan University,Wuxi 214122,China;Jiangsu Provincial Key Laboratory of Food Manufacturing Equipment,Wuxi 214122,China)
出处
《现代制造工程》
CSCD
北大核心
2024年第4期33-42,共10页
Modern Manufacturing Engineering
关键词
分布式柔性作业车间
多目标优化
变邻域搜索
自适应附加变量
distributed and flexible job-shop
multi-objective optimization
variable neighborhood search
adaptive additional variable
作者简介
孙鸿羽,硕士研究生,主要研究方向为智能制造。E-mail:shy3915251199@163.com;吉卫喜,教授,博士生导师,主要研究方向为智能制造技术与集成制造技术、数字化制造技术。
