摘要
针对柔性作业车间调度计算复杂度高,求解困难的难题,在分析竞争群优化算法的基础上,提出一种混合竞争群优化算法。首先,结合两段式编码设计了一种基于最小工序完工时间的机器选择策略,将连续的竞争群优化算法离散化;然后,将POX交叉与环形拓扑结构相结合,并引入邻域搜索,应用于优胜个体的更新,增强算法的全局搜索能力和局部搜索能力。最后通过案例测试并与其他算法比较,验证了混合竞争群优化算法对柔性作业车间调度问题具有较高的求解质量和稳定性。
Based on the analysis of competitive swarm optimizer, a hybrid competitive swarm optimizer is proposed to solve the disadvantages of high computational complexity and difficulty in flexible job-shop scheduling. Firstly, a two-phase encoding method is employed, and a machine selection strategy based on minimum process completion time is designed to discretize the continuous competitive swarm optimizer. Then, the precedence operation crossover(POX) is combined with ring topology, and neighborhood search is introduced to update the winning individual, so as to enhance the global search ability and local search ability of the algorithm. Lastly, through case testing and comparison with other algorithms, it is proved that the hybrid competitive swarm optimizer has high solution quality and stability for the flexible job-shop scheduling problem.
作者
张桐瑞
吴定会
ZHANG Tong-rui;WU Ding-hui(Key Laboratory of Advanced Process Control for Light Industry Ministry of Education,Jiangnan University,Wuxi 214122,China)
出处
《控制工程》
CSCD
北大核心
2021年第9期1820-1828,共9页
Control Engineering of China
基金
国家自然科学基金资助项目(61572237)。
关键词
柔性作业车间调度
竞争群优化算法
环形拓扑
邻域搜索
机器选择策略
flexible job-shop scheduling
competitive swarm optimizer
ring topology
neighborhood search
machine selection strategy
