An Improved Compact Genetic Algorithm for Scheduling Problems in a Flexible Flow Shop with a Multi-Queue Buffer
文献类型：期刊论文
| 作者 | Zhang Q(张权)3; Han ZH(韩忠华)1,2,3,4 ; Zhang, Jingyuan3; Shi HB(史海波)1,2,4
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| 刊名 | PROCESSES
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| 出版日期 | 2019 |
| 卷号 | 7期号:5页码:1-24 |
| 关键词 | flexible flow shop scheduling multi-queue limited buffers improved compact genetic algorithm probability density function of the Gaussian distribution |
| ISSN号 | 2227-9717 |
| 产权排序 | 1 |
| 英文摘要 | Flow shop scheduling optimization is one important topic of applying artificial intelligence to modern bus manufacture. The scheduling method is essential for the production efficiency and thus the economic profit. In this paper, we investigate the scheduling problems in a flexible flow shop with setup times. Particularly, the practical constraints of the multi-queue limited buffer are considered in the proposed model. To solve the complex optimization problem, we propose an improved compact genetic algorithm (ICGA) with local dispatching rules. The global optimization adopts the ICGA, and the capability of the algorithm evaluation is improved by mapping the probability model of the compact genetic algorithm to a new one through the probability density function of the Gaussian distribution. In addition, multiple heuristic rules are used to guide the assignment process. Specifically, the rules include max queue buffer capacity remaining (MQBCR) and shortest setup time (SST), which can improve the local dispatching process for the multi-queue limited buffer. We evaluate our method through the real data from a bus manufacture production line. The results show that the proposed ICGA with local dispatching rules and is very efficient and outperforms other existing methods. |
| WOS关键词 | OPTIMIZATION |
| 资助项目 | Liaoning Provincial Science Foundation, China[2018106008] ; Natural Science Foundation of China[61873174] ; Project of Liaoning Province Education Department, China[LJZ2017015] ; Shenyang Municipal Science and Technology Project, China[Z18-5-102] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000470965600061 |
| 源URL | [http://ir.sia.cn/handle/173321/24948]  |
| 专题 | 沈阳自动化研究所_数字工厂研究室 |
| 通讯作者 | Zhang Q(张权) |
| 作者单位 | 1.Institutes for Robotics and IntelligentManufacturing, Chinese Academy of Sciences, Shenyang 110016, China 2.Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang 110016, China 3.Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China 4.Department of Digital Factory, Shenyang Institute of Automation, the Chinese Academy of Sciences (CAS), Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Zhang Q,Han ZH,Zhang, Jingyuan,et al. An Improved Compact Genetic Algorithm for Scheduling Problems in a Flexible Flow Shop with a Multi-Queue Buffer[J]. PROCESSES,2019,7(5):1-24. |
| APA | Zhang Q,Han ZH,Zhang, Jingyuan,&Shi HB.(2019).An Improved Compact Genetic Algorithm for Scheduling Problems in a Flexible Flow Shop with a Multi-Queue Buffer.PROCESSES,7(5),1-24. |
| MLA | Zhang Q,et al."An Improved Compact Genetic Algorithm for Scheduling Problems in a Flexible Flow Shop with a Multi-Queue Buffer".PROCESSES 7.5(2019):1-24. |
入库方式： OAI收割
来源：沈阳自动化研究所
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