Institutional Repository of Digital Factory Department
| 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 | |
| Department | 数字工厂研究室 |
| Conference Name | 9th International Conference on Modelling, Identification and Control, ICMIC 2017 |
| Conference Date | July 10-12, 2017 |
| Conference Place | Kunming, China |
| Source Publication | Lecture Notes in Electrical Engineering |
| Publisher | Springer Verlag |
| Publication Place | Singapore |
| 2017 | |
| Pages | 273-289 |
| Indexed By | EI |
| EI Accession number | 20181805112284 |
| Contribution Rank | 1 |
| ISSN | 1876-1100 |
| ISBN | 978-981-10-7211-6 |
| Keyword | multi-objective differential evolution hybrid flow shop |
| Abstract | 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. |
| Language | 英语 |
| Document Type | 会议论文 |
| Identifier | http://ir.sia.cn/handle/173321/22052 |
| Collection | 数字工厂研究室 |
| Corresponding Author | Han ZH(韩忠华) |
| Affiliation | 1.Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, China; 2.Department of Digital Factory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China; 3.Sichuan College of Architectural Technology, Sichuan, China; 4.Virginia Tech, Blacksburg, VA, United States |
| Recommended Citation 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]. Singapore:Springer Verlag,2017:273-289. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| Improved NSGA-II alg（449KB） | 会议论文 | 开放获取 | CC BY-NC-SA | View Download | ||
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