| An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling | |
| Wu, Peiliang1,2,3,4; Yang, Qingyu1; Chen, Wenbai5; Mao, Bingyi1,3; Yu, Hongnian4 | |
| 发表期刊 | COMPLEXITY
 |
| ISSN | 1076-2787 |
| 2020-11-28 | |
| 卷号 | 2020页码:15 |
| 通讯作者 | Yu, Hongnian(yu61150@ieee.org) |
| 摘要 | Due to the NP-hard nature, the permutation flowshop scheduling problem (PFSSP) is a fundamental issue for Industry 4.0, especially under higher productivity, efficiency, and self-managing systems. This paper proposes an improved genetic-shuffled frog-leaping algorithm (IGSFLA) to solve the permutation flowshop scheduling problem. In the proposed IGSFLA, the optimal initial frog (individual) in the initialized group is generated according to the heuristic optimal-insert method with fitness constrain. The crossover mechanism is applied to both the subgroup and the global group to avoid the local optimal solutions and accelerate the evolution. To evolve the frogs with the same optimal fitness more outstanding, the disturbance mechanism is applied to obtain the optimal frog of the whole group at the initialization step and the optimal frog of the subgroup at the searching step. The mathematical model of PFSSP is established with the minimum production cycle (makespan) as the objective function, the fitness of frog is given, and the IGSFLA-based PFSSP is proposed. Experimental results have been given and analyzed, showing that IGSFLA not only provides the optimal scheduling performance but also converges effectively. |
| DOI | 10.1155/2020/3450180 |
| 关键词[WOS] | BEE COLONY ALGORITHM ; SHOP ; OPTIMIZATION |
| 收录类别 | SCI |
| 语种 | 英语 |
| 资助项目 | National Key R&D Program of China[2018YFB1308300] ; European Commission[H2020-MSCA-RISE-2016-734875] ; China Postdoctoral Science Foundation[2018M631620] ; Natural Science Foundation of Beijing Municipality[4202026] ; Doctoral Fund of Yanshan University[BL18007] |
| 项目资助者 | National Key R&D Program of China ; European Commission ; China Postdoctoral Science Foundation ; Natural Science Foundation of Beijing Municipality ; Doctoral Fund of Yanshan University |
| WOS研究方向 | Mathematics ; Science & Technology - Other Topics |
| WOS类目 | Mathematics, Interdisciplinary Applications ; Multidisciplinary Sciences |
| WOS记录号 | WOS:000597936600003 |
| 出版者 | WILEY-HINDAWI |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/42671 |
| 专题 | 复杂系统管理与控制国家重点实验室 |
| 通讯作者 | Yu, Hongnian |
| 作者单位 | 1.Yanshan Univ, Sch Informat Sci & Engn, Qinhuangdao 066004, Hebei, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Key Lab Comp Virtual Technol & Syst Integrat Hebe, Qinhuangdao 066004, Hebei, Peoples R China 4.Edinburgh Napier Univ, Sch Engn & Built Environm, Edinburgh EH10 5DT, Midlothian, Scotland 5.Beijing Informat Sci & Technol Univ, Sch Automat, Beijing 100101, Peoples R China |
| 第一作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Wu, Peiliang,Yang, Qingyu,Chen, Wenbai,et al. An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling[J]. COMPLEXITY,2020,2020:15. |
| APA | Wu, Peiliang,Yang, Qingyu,Chen, Wenbai,Mao, Bingyi,&Yu, Hongnian.(2020).An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling.COMPLEXITY,2020,15. |
| MLA | Wu, Peiliang,et al."An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling".COMPLEXITY 2020(2020):15. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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