Bat algorithm: a novel approach for global engineering optimization

Purpose - Nature-inspired algorithms are among the most powerful algorithms for optimization. The purpose of this paper is to introduce a new nature-inspired metaheuristic optimization algorithm, called bat algorithm (BA), for solving engineering optimization tasks.Design methodology approach - The...

Full description

Saved in:
Bibliographic Details
Published inEngineering computations Vol. 29; no. 5; pp. 464 - 483
Main Authors Yang, Xin-She, Hossein Gandomi, Amir
Format Journal Article
LanguageEnglish
Published Bradford Emerald Group Publishing Limited 13.07.2012
Subjects
Algorithms
Bats
Design optimization
Engineering
Formulations
Heuristic
Mathematical models
Nonlinearity
Optimization
Searching
Signal processing
Studies
Tasks
Optimization techniques
Bat algorithm
Iterative methods
Metaheuristic algorithm
Programming and algorithm theory
Engineering optimization
Online AccessGet full text

Cover

More Information
Summary:Purpose - Nature-inspired algorithms are among the most powerful algorithms for optimization. The purpose of this paper is to introduce a new nature-inspired metaheuristic optimization algorithm, called bat algorithm (BA), for solving engineering optimization tasks.Design methodology approach - The proposed BA is based on the echolocation behavior of bats. After a detailed formulation and explanation of its implementation, BA is verified using eight nonlinear engineering optimization problems reported in the specialized literature.Findings - BA has been carefully implemented and carried out optimization for eight well-known optimization tasks; then a comparison has been made between the proposed algorithm and other existing algorithms.Originality value - The optimal solutions obtained by the proposed algorithm are better than the best solutions obtained by the existing methods. The unique search features used in BA are analyzed, and their implications for future research are also discussed in detail.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ISSN:0264-4401
1758-7077
DOI:10.1108/02644401211235834