Fuzzy adaptive teaching–learning-based optimization for global numerical optimization

Teaching–learning-based optimization (TLBO) is one of the latest metaheuristic algorithms being used to solve global optimization problems over continuous search space. Researchers have proposed few variants of TLBO to improve the performance of the basic TLBO algorithm. This paper presents a new va...

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Bibliographic Details
Published in:Neural computing & applications Vol. 29; no. 2; pp. 309 - 327
Main Authors: Cheng, Min-Yuan, Prayogo, Doddy
Format: Journal Article
Language:English
Published: London Springer London 01.01.2018
Springer Nature B.V
Subjects:
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Global optimization
Heuristic methods
Image Processing and Computer Vision
Machine learning
Mathematical analysis
Nonlinear programming
Operators (mathematics)
Original Article
Performance enhancement
Probability and Statistics in Computer Science
Fuzzy logic
Metaheuristic
Global optimization
Teaching–learning-based optimization
Parameter tuning
ISSN:0941-0643, 1433-3058
Online Access:Get full text
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Summary:Teaching–learning-based optimization (TLBO) is one of the latest metaheuristic algorithms being used to solve global optimization problems over continuous search space. Researchers have proposed few variants of TLBO to improve the performance of the basic TLBO algorithm. This paper presents a new variant of TLBO called fuzzy adaptive teaching–learning-based optimization (FATLBO) for numerical global optimization. We propose three new modifications to the basic scheme of TLBO in order to improve its searching capability. These modifications consist, namely of a status monitor, fuzzy adaptive teaching–learning strategies, and a remedial operator. The performance of FATLBO is investigated on four experimental sets comprising complex benchmark functions in various dimensions and compared with well-known optimization methods. Based on the results, we conclude that FATLBO is able to deliver excellence and competitive performance for global optimization.
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ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-016-2449-7