文献类型：期刊文献

英文题名：Self-adaptive multi-objective teaching-learning-based optimization and its application in ethylene cracking furnace operation optimization

作者：Yu, Kunjie[1];Wang, Xin[2];Wang, Zhenlei[1]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Shanghai Jiao Tong Univ, Ctr Elect & Elect Technol, Shanghai 200240, Peoples R China

年份：2015

卷号：146

起止页码：198

外文期刊名：CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

收录：;EI(收录号：20242616502109);WOS:【SCI-EXPANDED(收录号:WOS:000360595100022)】；

基金：This research was supported by Major State Basic Research Development Program of China under Grant No. 2012CB720500, National Natural Science Foundation of China under Grant Nos. 21276078, 61422303, Shanghai Municipal Science and Technology Commission under Grant No. 13111103800, Fundamental Research Funds for the Central Universities, Shanghai Natural Science Foundation under Grant No. 14ZR1421800, and the State Key Laboratory of Synthetical Automation for Process Industries under Grant No. PAL-N201404.

语种：英文

外文关键词：Multi-objective optimization; Teaching-learning-based optimization; Cracking furnace; Operation optimization

摘要：A self-adaptive multi-objective teaching-learning-based optimization (SA-MTLBO) is proposed in this paper. In SA-MTLBO, the learners can self-adaptively select the modes of learning according to their levels of knowledge in classroom. The excellent learners are more likely to choose the learner phase to enhance population diversity, and the common learners are tend to choose the teacher phase to improve the convergence ability of the algorithm. So learners at different levels choose appropriate modes of learning and carry out corresponding search function to efficiently enhance the performance of algorithm. To evaluate the effectiveness of the proposed algorithm, SA-MTLBO is firstly compared with other algorithms in twelve test problems. The results demonstrate that SA-MTLBO can generate Pareto optimal fronts with good convergence and distribution. Finally, SA-MTLBO is used to maximize the yields of ethylene, propylene, and butadiene of the naphtha pyrolysis process. The computational results of SA-MTLBO indicate that the operation of ethylene cracking furnace can be improved by increasing the yields of ethylene, propylene, and butadiene. (C) 2015 Elsevier B.V. All rights reserved.