Knowledge Management System Of Institute of process engineering,CAS
| Stakeholder-oriented multi-objective process optimization based on an improved genetic algorithm | |
| Su, Yang1,2; Jin, Saimeng1,2; Zhang, Xiangping3; Shen, Weifeng1,2; Eden, Mario R.4; Ren, Jingzheng5 | |
| 2020-01-04 | |
| Source Publication | COMPUTERS & CHEMICAL ENGINEERING
 |
| ISSN | 0098-1354 |
| Volume | 132Pages:16 |
| Abstract | Multi-objective optimization (MOO) is frequently used to solve many practical problems of chemical processes but process designers only need a limited number of valuable solutions in the final results. In this study, an optimization strategy associated with an improved genetic algorithm was developed to search valuable solutions for stakeholders' preference more purposefully. The algorithm was improved to reduce overlapping solutions as a result of the discrete variables in practical problems, and it allowed users to set a reference point or an angle associated with a reference point to make solutions converge into the preferred spaces. Three test functions and two practical problems were used to highlight that the proposed strategy could make designers optimize processes more efficiently. Especially, the angle-based algorithm could be more effective than the distance-based one on the tri-objective problems. Thus, the developed strategy is robust in the optimization of processes assisted with the designer's preference. (C) 2019 Elsevier Ltd. All rights reserved. |
| Keyword | Multi-objective optimization Preference Process optimization Genetic algorithm |
| DOI | 10.1016/j.compchemeng.2019.106618 |
| Language | 英语 |
| WOS Keyword | EXTRACTIVE DISTILLATION ; OPTIMAL-DESIGN ; AZEOTROPES |
| Funding Project | National Natural Science Foundation of China[21878028] ; National Natural Science Foundation of China[21606026] ; Fundamental Research Funds for the Central Universities[2019CDQYHG021] ; Beijing Hundreds of Leading Talents Training Project of Science and Technology[Z17110 0001117154] |
| WOS Research Area | Computer Science ; Engineering |
| WOS Subject | Computer Science, Interdisciplinary Applications ; Engineering, Chemical |
| Funding Organization | National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; Beijing Hundreds of Leading Talents Training Project of Science and Technology |
| WOS ID | WOS:000498396100020 |
| Publisher | PERGAMON-ELSEVIER SCIENCE LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ipe.ac.cn/handle/122111/38419 |
| Collection | 中国科学院过程工程研究所 |
| Corresponding Author | Shen, Weifeng |
| Affiliation | 1.Chongqing Univ, Sch Chem & Chem Engn, Chongqing 400044, Peoples R China 2.Chongqing Univ, Natl Municipal Joint Engn Lab Chem Proc Intensifi, Chongqing 400044, Peoples R China 3.Chinese Acad Sci, Inst Proc Engn, Beijing Key Lab Ion Liquids Clean Proc, CAS Key Lab Green Proc & Engn, Beijing 100190, Peoples R China 4.Auburn Univ, Dept Chem Engn, Auburn, AL 36849 USA 5.Hong Kong Polytech Univ, Dept Ind & Syst Engn, Hong Kong, Peoples R China |
| Recommended Citation GB/T 7714 | Su, Yang,Jin, Saimeng,Zhang, Xiangping,et al. Stakeholder-oriented multi-objective process optimization based on an improved genetic algorithm[J]. COMPUTERS & CHEMICAL ENGINEERING,2020,132:16. |
| APA | Su, Yang,Jin, Saimeng,Zhang, Xiangping,Shen, Weifeng,Eden, Mario R.,&Ren, Jingzheng.(2020).Stakeholder-oriented multi-objective process optimization based on an improved genetic algorithm.COMPUTERS & CHEMICAL ENGINEERING,132,16. |
| MLA | Su, Yang,et al."Stakeholder-oriented multi-objective process optimization based on an improved genetic algorithm".COMPUTERS & CHEMICAL ENGINEERING 132(2020):16. |
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