舰船电子工程2024，Vol.44Issue(4)：188-193,6.DOI:10.3969/j.issn.1672-9730.2024.04.039
聚类和NSGA-Ⅱ联合算法在混合流水车间的应用研究
Application Research of Clustering and NSGA-Ⅱ Joint Algorithm in Hybrid Flow Shop
摘要
Abstract
In order to improve the scheduling difficulty of mixed-flow production in the final assembly shop of a high-end equipment manufacturing enterprise,the difficulty of product group batch in the batch processing stage and realize the joint optimi-zation of multi-objective in the workshop,this paper investigates the multi-objective optimization problem of hybrid flow shop with batch processors.Firstly,a multi-objective optimization model is established according to the operation situation of the workshop,and then a joint method based on K-means clustering algorithm and non-dominated sorting Genetic Algorithm ⅱ(NSGA-Ⅱ)is proposed.A clustering process is designed to group incompatible products,and a double-layer coding method based on product group number and product number within the group is designed.A complete group batch process is designed for batch operations.Fi-nally,the workshop production case is used to test,and the results are compared with the results obtained by only using NSGA-Ⅱ,which verifies the effectiveness of the proposed method.关键词
混合流水车间/并行批处理机/非支配排序遗传算法/K-means算法Key words
hybrid flow shop/parallel batch processing machine/non-dominated sorting genetics algorithm/K-means al-gorithm分类
通用工业技术引用本文复制引用
韩树贤,赵文普,闫华..聚类和NSGA-Ⅱ联合算法在混合流水车间的应用研究[J].舰船电子工程,2024,44(4):188-193,6.基金项目
国家基础科研重点项目(编号:JCKY2019205B012)资助. （编号:JCKY2019205B012）
