A novel fuzzy adaptive teaching–learning-based optimization (FATLBO) for solving structural optimization problems

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• 作者：Min-Yuan Cheng ; Doddy Prayogo
• 关键词：Optimization ; Fuzzy logic ; Teaching–learning ; based optimization ; Structural design problems
• 刊名：Engineering with Computers
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：33
• 期：1
• 页码：55-69
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Computer-Aided Engineering (CAD, CAE) and Design; Math. Applications in Chemistry; Systems Theory, Control; Calculus of Variations and Optimal Control; Optimization; Classical Mechanics; Appl.Mathemat
• 出版者：Springer London
• ISSN：1435-5663
• 卷排序：33

文摘

This paper presents a new optimization algorithm called fuzzy adaptive teaching–learning-based optimization (FATLBO) for solving numerical structural problems. This new algorithm introduces three new mechanisms for increasing the searching capability of teaching–learning-based optimization namely status monitor, fuzzy adaptive teaching–learning strategies, and remedial operator. The performance of FATLBO is compared with well-known optimization methods on 26 unconstrained mathematical problems and five structural engineering design problems. Based on the obtained results, it can be concluded that FATLBO is able to deliver excellence and competitive performance in solving various structural optimization problems.