中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Improved NSGA-II algorithm for multi-objective scheduling problem in hybrid flow shop

文献类型:会议论文

作者Han ZH(韩忠华)2,5; Wang, Shiyao2; Dong XT(董晓婷)3; Ma, Xiaofu1
出版日期2017
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
关键词multi-objective differential evolution hybrid flow shop
页码740-745
通讯作者Han ZH(韩忠华)
中文摘要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.
收录类别EI
产权排序1
会议录Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017
会议录出版者IEEE
会议录出版地New York
语种英语
ISBN号978-1-5090-6573-8
源URL[http://ir.sia.cn/handle/173321/22420]  
专题沈阳自动化研究所_广州中国科学院沈阳自动化研究所分所
作者单位1.Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA
2.Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, China
3.Department of Electrical Engineering, College of Architectural Technology, Sichuan, China
4.24060, United States
5.Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang, China
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]. 见:9th International Conference on Modelling, Identification and Control, ICMIC 2017. Kunming, China. July 10-12, 2017.

入库方式: OAI收割

来源:沈阳自动化研究所

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