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An improved multi-objective optimization algorithm for solving flexible job shop scheduling problem with variable batches 被引量:2
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作者 WU Xiuli PENG Junjian +2 位作者 XIE Zirun ZHAO Ning WU Shaomin 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2021年第2期272-285,共14页
In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop pro... In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop problem with the variable batches scheduling model is formulated.Second,we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method.Moreover,in order to increase the diversity of the population,two methods are developed.One is the threshold to control the neighborhood updating,and the other is the dynamic clustering algorithm to update the population.Finally,a group of experiments are carried out.The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively,and has effective performance in solving the flexible job shop scheduling problem with variable batches. 展开更多
关键词 flexible job shop variable batch inverse scheduling multi-objective evolutionary algorithm based on decomposition a batch optimization algorithm with inverse scheduling
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