KMS Of Academy of mathematics and systems sciences, CAS
An effective hybrid particle swarm optimization for batch scheduling of polypropylene processes | |
Liu, Bo1,2,3; Wang, Ling1; Liu, Ying4; Qian, Bin5; Jin, Yi-Hui1 | |
2010-04-05 | |
发表期刊 | COMPUTERS & CHEMICAL ENGINEERING |
ISSN | 0098-1354 |
卷号 | 34期号:4页码:518-528 |
摘要 | Short-term scheduling for batch processes which allocates a set of limited resources over time to manufacture one or more products plays a key role in batch processing systems of the enterprise for maintaining competitive position in fast changing market. This paper proposes an effective hybrid particle swarm optimization (HPSO) algorithm for polypropylene (PP) batch industries to minimize the maximum completion time, which is modeled as a complex generalized multi-stage flow shop scheduling problem with parallel units at each stage and different inventory storage policies In HPSO. a novel encoding scheme based on random key representation, a new assignment scheme STPT (smallest starting processing time) by taking the different intermediate storage strategies into account, an effective local search based on the Nawaz-Enscore-Ham (NEH) heuristic, as well as a local search based on simulated annealing with an adaptive meta-Lamarckian learning strategy are proposed Simulation results based on a set of random instances and comparisons with several adaptations of constructive methods and meta-heuristics demonstrate the effectiveness of the proposed HPSO (C) 2010 Elsevier Ltd. All rights reserved |
关键词 | Particle swarm optimization Polypropylene batch Batch scheduling Multi-stage flow shop Hybrid flow shop Simulated annealing Zero-wait No intermediate storage |
DOI | 10.1016/j.compchemeng.2009.12.010 |
语种 | 英语 |
资助项目 | National Science Foundation of China[70871065] ; National Science Foundation of China[60834004] ; National Science Foundation of China[60774082] ; National Science Foundation of China[60704032] ; National Science Foundation of China[60904081] |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Interdisciplinary Applications ; Engineering, Chemical |
WOS记录号 | WOS:000276426900011 |
出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.amss.ac.cn/handle/2S8OKBNM/10614 |
专题 | 中国科学院数学与系统科学研究院 |
通讯作者 | Liu, Bo |
作者单位 | 1.Tsinghua Univ, Dept Automat, TNList, Beijing 100084, Peoples R China 2.Chinese Acad Sci, Ctr Forecasting Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China 3.Chinese Acad Sci, Ctr Chinese Agr Policy, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 4.Beijing Jiaotong Univ, CCISR, Beijing 100044, Peoples R China 5.Kunming Univ Sci & Technol, Dept Automat, Kunming 650051, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Bo,Wang, Ling,Liu, Ying,et al. An effective hybrid particle swarm optimization for batch scheduling of polypropylene processes[J]. COMPUTERS & CHEMICAL ENGINEERING,2010,34(4):518-528. |
APA | Liu, Bo,Wang, Ling,Liu, Ying,Qian, Bin,&Jin, Yi-Hui.(2010).An effective hybrid particle swarm optimization for batch scheduling of polypropylene processes.COMPUTERS & CHEMICAL ENGINEERING,34(4),518-528. |
MLA | Liu, Bo,et al."An effective hybrid particle swarm optimization for batch scheduling of polypropylene processes".COMPUTERS & CHEMICAL ENGINEERING 34.4(2010):518-528. |
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