摘要
针对多目标柔性作业车间调度问题,以最小化最大完工时间、最小化机器总负荷、最小化机器最大负荷为目标,提出一种改进邻域结构的离散萤火虫算法。首先,采用多种策略相结合的方式初始化种群,提高算法初始解质量以及种群多样性;其次,通过改进关键路径的邻域结构并设计离散萤火虫算法的位置更新公式,以增强算法全局搜索和局部搜索能力;最后,将该算法应用于标准数据集,并将求解结果与其他算法进行对比,验证了所提算法的有效性。
For the multi-objective flexible job shop scheduling problem,with the goal of minimizing the maximum completion time,minimizing the total load of the machine,and minimizing the maximum load of the machine,a discrete firefly algorithm with improved neighborhood structure is proposed.Firstly,a combination of multiple strategies is used to initialize the population to improve the quality of the initial solution of the algorithm and the diversity of the population.Secondly,by improving the neighborhood structure of the critical path and designing the position update formula of the discrete firefly algorithm to enhance the algorithm’s global search and local search ability.Finally,the algorithm is applied to the standard data set,and the solution results are compared with other algorithms to verify the effectiveness of the proposed algorithm.
作者
郑捷
潘大志
ZHENG Jie;PAN Dazhi(College of Mathematics and Information,China West Normal University,Nanchong 637009,China;Key Laboratory of Optimization Theory and Applications in Sichuan Provincial Universities,China West Normal University,Nanchong 637009,China)
出处
《控制工程》
CSCD
北大核心
2024年第2期272-280,共9页
Control Engineering of China
基金
国家自然科学基金资助项目(11871059)
四川省教育厅自然科学基金资助项目(18ZA0469)
西华师范大学英才科研基金项目(17YC385)。
关键词
多目标
柔性作业车间调度问题
关键路径
邻域结构
离散萤火虫算法
Multi-objective
flexible job shop scheduling problem
critical path
neighborhood structure
discrete firefly algorithm
