求解模糊作业车间调度问题的混沌乌鸦搜索算法

Chaotic crow search algorithm for fuzzy job-shop scheduling

为求解模糊作业车间调度问题(FJSSP),提出了一种改进的混沌乌鸦搜索算法(CCSA)。算法采用基于工序的编码,并设计了一种修补方式以使CCSA有效求解FJSSP;为增强算法的邻域搜索能力引入了变异算子;为提高算法的进化能力,提出了基于余弦相似度的多样最优个体集来引导进化,使在增强进化效率的同时保证种群多样性;为进一步提高算法在求解FJSSP时的搜索效率,提出了一种基于机器空闲缩小的搜索方法。最后选取了5个典型实例进行了测试,实验结果验证了所提算法的有效性。

An improved chaotic crow search algorithm(CCSA)is proposed for solving the fuzzy job-shop scheduling problem(FJSSP).The algorithm adopts the process-based coding method, and a solution-correct way is designed to make CCSA solve FJSSP effectively.In order to enhance the neighborhood search ability of the algorithm, the mutation operator is introduced.In order to improve the evolutionary ability of the algorithm, multiple optimal individual set based on the Cosine Similarity is proposed to guide the evolution, which not only enhanced the evolutionary efficiency but also ensures the diversity of the population.In order to further improve the search efficiency of CCSA when solving FJSSP,a search method based on the reduction of machine’s spare time is proposed.Finally, five benchmark problems are selected for testing, and the results verify the effectiveness of the proposed algorithm.