文献类型：期刊文献

英文题名：Many-Objective Optimization of Distributed Heterogeneous Hybrid Flowshop Lot-Streaming Scheduling Problem with Missing Operations

作者：Chen, Sanyan[1]; Wang, Xuewu[1]; Wang, Ye[1]; Gu, Xingsheng[1]

机构：[1] East China University of Science and Technology, Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China

年份：2024

起止页码：443

外文期刊名：2024 8th International Conference on Robotics, Control and Automation, ICRCA 2024

收录：EI(收录号：20243817053383)

语种：英文

外文关键词：Competition - Concrete construction - Job shop scheduling - Scheduling algorithms

摘要：The distributed heterogeneous hybrid flowshop lot-streaming scheduling problem with missing operations (DHHFLSPMO), a common occurrence in manufacturing sectors like stainless steel factory and steel furniture manufacturing factory, has not been widely investigated. In this paper, a many-objective evolutionary algorithm based on multiple populations collaborative search (MaEA/MPCS) is proposed to solve the DHHFLSPMO with the criteria of minimizing makespan, total flow time, total weighted earliness and tardiness, and idle time of machines. First, four populations are utilized to optimize the four objectives individually. Second, one population interacts with another to avoid overly focusing on one objective during the course of evolution. Third, an archive is established to collect all the nondominated solutions, and is updated using fast nondominate sorting method and crowding distance. Finally, the computational simulation is conducted, and the results demonstrate that the proposed MaEA/MPCS surpasses its competitors by a significant margin. ? 2024 IEEE.