模糊分布式柔性作业车间调度问题的求解算法

An improved GWO algorithm for fuzzy distributed flexible job shop scheduling problem

针对加工时间不确定的模糊分布式柔性作业车间调度问题,在引入三角模糊数的基础上,提出了一种改进的灰狼优化算法以最小化最大模糊完工时间.该算法的主要特点是设计了一种基于工序、工厂和机器的三层编码方案,提出了一种混合初始化策略以提高种群质量,采用基于非线性函数和动态权重的更新机制协调算法的全局探索和局部开发能力,提出四种邻域搜索结构提高解的质量.最后通过不同规模的仿真对比实验,验证了该算法在求解模糊分布式柔性作业车间调度问题上的有效性和优越性.

For the fuzzy distributed flexible job shop scheduling problem with uncertain processing time,an improved gray wolf optimization algorithm was proposed based on the introduction of triangular fuzzy number to minimize the maximum fuzzy completion time. In improved gray wolf optimization algorithm,a three-layer coding scheme based on operation,factory and machine was designed,a hybrid initialization strategy was proposed to improve the quality of population,the updating mechanism based on nonlinear function and dynamic weight was introduced to coordinate the global exploration capability and local development capability of the algorithm and four neighborhood search structures were proposed to improve the quality of solutions.Finally,the effectiveness and superiority of the algorithm in solving the fuzzy distributed flexible job shop scheduling problem were verified through simulation comparison experiments of different scales.