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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Vydané v:	Engineering optimization Ročník 50; číslo 4; s. 716 - 731
Hlavní autori:	Guo, Zhan, Yan, Xuefeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Abingdon Taylor & Francis 03.04.2018 Taylor & Francis Ltd
Predmet:	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
On-line prístup:	Získať plný text
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