Improved NSGA-II algorithm for multi-objective scheduling problem in hybrid flow shop
文献类型：会议论文
| 作者 | Wang, Shiyao; Ma, Xiaofu; Dong XT(董晓婷); Han ZH(韩忠华); Zhang HL(张华良) ; Ceng P(曾鹏); Yu HB(于海斌); Yang F(杨帆)
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| 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 | 273-289 |
| 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 is investigated. 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 basic 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 further improve the MODADE algorithm by integrating the AP clustering mechanism. We compare the proposed algorithm and compare it with the state-of-the-art solutions. 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 | Lecture Notes in Electrical Engineering
 |
| 会议录出版者 | Springer Verlag |
| 会议录出版地 | Singapore |
| 语种 | 英语 |
| ISSN号 | 1876-1100 |
| ISBN号 | 978-981-10-7211-6 |
| 源URL | [http://ir.sia.cn/handle/173321/22029]  |
| 专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
| 作者单位 | 1.Virginia Tech, Blacksburg, VA, United States 2.Sichuan College of Architectural Technology, Sichuan, China 3.Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, China 4.Department of Digital Factory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Wang, Shiyao,Ma, Xiaofu,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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