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Improved NSGA-II algorithm for multi-objective scheduling problem in hybrid flow shop
Han ZH(韩忠华)1,2; Wang, Shiyao1; Dong XT(董晓婷)3; Ma, Xiaofu4
作者部门数字工厂研究室
会议名称9th International Conference on Modelling, Identification and Control, ICMIC 2017
会议日期July 10-12, 2017
会议地点Kunming, China
会议录名称Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017
出版者IEEE
出版地New York
2017
页码740-745
收录类别EI
EI收录号20183105619938
产权排序1
ISBN号978-1-5090-6573-8
关键词multi-objective differential evolution hybrid flow shop
摘要In this paper, multi-objective optimization for hybrid flow shop scheduling problem has been studied. The delivery time penalty and the load imbalance penalty are taken as the evaluation metrics. We describe the optimization framework for this hybrid flow shop problem, and design an improved NSGA-II algorithm for solution searching. Specifically, a multi-objective dynamic adaptive differential evolution algorithm (MODADE) is proposed to enhance the searching efficiency of the general differential evolution operations. MODADE calculates the similarity between different individuals based on their Hamming distance, and dynamically generates the high-similarity individuals for the population. We compare MODADE compared with the state-of-the-art algorithms, and the numerical result shows that the proposed MODADE algorithm outperforms others in terms of the algorithm convergence, the number and distribution of Pareto solutions.
语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/22359
专题数字工厂研究室
通讯作者Han ZH(韩忠华)
作者单位1.Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, China
2.Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang, China
3.Department of Electrical Engineering, College of Architectural Technology, Sichuan, China
4.Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA
5.24060, United States
推荐引用方式
GB/T 7714
Han ZH,Wang, Shiyao,Dong XT,et al. Improved NSGA-II algorithm for multi-objective scheduling problem in hybrid flow shop[C]. New York:IEEE,2017:740-745.
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