A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand
文献类型：期刊论文
| 作者 | Goli, Alireza1; Tirkolaee, Erfan Babaee2,3; Malmir, Behnam4; Bian, Gui-Bin5 ; Sangaiah, Arun Kumar6
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| 刊名 | COMPUTING
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| 出版日期 | 2019-06-01 |
| 卷号 | 101期号:6页码:499-529 |
| 关键词 | Aggregate production planning Uncertain seasonal demand Multi-objective invasive weed optimization algorithm (MOIWO) NSGA-II Robust optimization |
| ISSN号 | 0010-485X |
| DOI | 10.1007/s00607-018-00692-2 |
| 通讯作者 | Sangaiah, Arun Kumar(arunkumarsangaiah@gmail.com) |
| 英文摘要 | This paper addresses a robust multi-objective multi-period aggregate production planning (APP) problem based on different scenarios under uncertain seasonal demand. The main goals are to minimize the total cost including in-house production, outsourcing, workforce, holding, shortage and employment/unemployment costs, and maximize the customers' satisfaction level. To deal with demand uncertainty, robust optimization approach is applied to the proposed mixed integer linear programming model. A goal programming method is then implemented to cope with the multi-objectiveness and validate the suggested robust model. Since APP problems are classified as NP-hard, two solution methods of non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective invasive weed optimization algorithm (MOIWO) are designed to solve the problem. Moreover, Taguchi design method is implemented to increase the efficiency of the algorithms by adjusting the algorithms' parameters optimally. Finally, several numerical test problems are generated in different sizes to evaluate the performance of the algorithms. The results obtained from different comparison criteria demonstrate the high quality of the proposed solution methods in terms of speed and accuracy in finding optimal solutions. |
| WOS关键词 | SUPPLY CHAIN ; OBJECTIVE OPTIMIZATION ; GENETIC ALGORITHM ; MODEL |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000467041900002 |
| 出版者 | SPRINGER WIEN |
| 源URL | [http://ir.ia.ac.cn/handle/173211/24575]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 通讯作者 | Sangaiah, Arun Kumar |
| 作者单位 | 1.Yazd Univ, Dept Ind Engn, Yazd, Iran 2.Mazandaran Univ Sci & Technol, Dept Ind Engn, Babol Sar, Iran 3.Islamic Azad Univ, Ayatollah Amoli Branch, Young Researchers & Elite Club, Amol, Iran 4.Univ Virginia, Dept Syst & Informat Engn, Charlottesville, VA 22904 USA 5.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 6.Vellore Inst Technol, Sch Comp Sci & Engn, Vellore 632014, Tamil Nadu, India |
| 推荐引用方式 GB/T 7714 | Goli, Alireza,Tirkolaee, Erfan Babaee,Malmir, Behnam,et al. A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand[J]. COMPUTING,2019,101(6):499-529. |
| APA | Goli, Alireza,Tirkolaee, Erfan Babaee,Malmir, Behnam,Bian, Gui-Bin,&Sangaiah, Arun Kumar.(2019).A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand.COMPUTING,101(6),499-529. |
| MLA | Goli, Alireza,et al."A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand".COMPUTING 101.6(2019):499-529. |
入库方式： OAI收割
来源：自动化研究所
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