Bat algorithm for constrained optimization tasks

In this study, we use a new metaheuristic optimization algorithm, called bat algorithm (BA), to solve constraint optimization tasks. BA is verified using several classical benchmark constraint problems. For further validation, BA is applied to three benchmark constraint engineering problems reported...

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Veröffentlicht in:	Neural computing & applications Jg. 22; H. 6; S. 1239 - 1255
Hauptverfasser:	Gandomi, Amir Hossein, Yang, Xin-She, Alavi, Amir Hossein, Talatahari, Siamak
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer-Verlag 01.05.2013 Springer
Schlagworte:	Applied sciences Artificial Intelligence Calculus of variations and optimal control Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer science; control theory; systems Data Mining and Knowledge Discovery Exact sciences and technology Image Processing and Computer Vision Learning and adaptive systems Mathematical analysis Mathematics Numerical analysis Numerical analysis. Scientific computation Numerical methods in mathematical programming, optimization and calculus of variations Numerical methods in optimization and calculus of variations Original Article Probability and Statistics in Computer Science Sciences and techniques of general use Constraint optimization Metaheuristic algorithm Bat algorithm Engineering Neural computation Algorithm performance Optimal solution Optimization method Benchmarks Neural network Algorithm Constrained optimization
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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Abstract	In this study, we use a new metaheuristic optimization algorithm, called bat algorithm (BA), to solve constraint optimization tasks. BA is verified using several classical benchmark constraint problems. For further validation, BA is applied to three benchmark constraint engineering problems reported in the specialized literature. The performance of the bat algorithm is compared with various existing algorithms. The optimal solutions obtained by BA are found to be better than the best solutions provided by the existing methods. Finally, the unique search features used in BA are analyzed, and their implications for future research are discussed in detail.
AbstractList	In this study, we use a new metaheuristic optimization algorithm, called bat algorithm (BA), to solve constraint optimization tasks. BA is verified using several classical benchmark constraint problems. For further validation, BA is applied to three benchmark constraint engineering problems reported in the specialized literature. The performance of the bat algorithm is compared with various existing algorithms. The optimal solutions obtained by BA are found to be better than the best solutions provided by the existing methods. Finally, the unique search features used in BA are analyzed, and their implications for future research are discussed in detail.
Author	Yang, Xin-She Gandomi, Amir Hossein Alavi, Amir Hossein Talatahari, Siamak
Author_xml	– sequence: 1 givenname: Amir Hossein surname: Gandomi fullname: Gandomi, Amir Hossein email: a.h.gandomi@gmail.com organization: Young Researchers Club, Central Tehran Branch, Islamic Azad University – sequence: 2 givenname: Xin-She surname: Yang fullname: Yang, Xin-She organization: Mathematics and Scientific Computing, National Physical Laboratory – sequence: 3 givenname: Amir Hossein surname: Alavi fullname: Alavi, Amir Hossein organization: Young Researchers Club, Mashhad Branch, Islamic Azad University – sequence: 4 givenname: Siamak surname: Talatahari fullname: Talatahari, Siamak organization: Marand Faculty of Engineering, University of Tabriz
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Keywords	Constraint optimization Metaheuristic algorithm Bat algorithm Engineering Neural computation Algorithm performance Optimal solution Optimization method Benchmarks Neural network Algorithm Constrained optimization
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Snippet	In this study, we use a new metaheuristic optimization algorithm, called bat algorithm (BA), to solve constraint optimization tasks. BA is verified using...
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SubjectTerms	Applied sciences Artificial Intelligence Calculus of variations and optimal control Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer science; control theory; systems Data Mining and Knowledge Discovery Exact sciences and technology Image Processing and Computer Vision Learning and adaptive systems Mathematical analysis Mathematics Numerical analysis Numerical analysis. Scientific computation Numerical methods in mathematical programming, optimization and calculus of variations Numerical methods in optimization and calculus of variations Original Article Probability and Statistics in Computer Science Sciences and techniques of general use
Title	Bat algorithm for constrained optimization tasks
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