Optimization of the p-xylene oxidation process by a multi-objective differential evolution algorithm with adaptive parameters co-derived with the population-based incremental learning algorithm

Different operating conditions of p-xylene oxidation have different influences on the product, purified terephthalic acid. It is necessary to obtain the optimal combination of reaction conditions to ensure the quality of the products, cut down on consumption and increase revenues. A multi-objective...

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Bibliographic Details
Published in:	Engineering optimization Vol. 50; no. 4; pp. 716 - 731
Main Authors:	Guo, Zhan, Yan, Xuefeng
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 03.04.2018 Taylor & Francis Ltd
Subjects:	Adaptive algorithms Algorithms Chemical industry Computer simulation differential evolution algorithm Evolutionary algorithms Machine learning multi-objective optimization problems Multiple objective analysis Optimization Oxidation p-Xylene oxidation process Population (statistical) population-based incremental learning algorithm self-adaptive Statistical analysis Terephthalic acid Xylene
ISSN:	0305-215X, 1029-0273
Online Access:	Get full text
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