Bat algorithm: a novel approach for global engineering optimization
Алгоритм летучих мышей: новый подход к глобальной инженерной оптимизации
2012-07-13
SCID: 54.1/3vupjx9s
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bat algorithmecholocation behaviorglobal engineering optimizationnature-inspired metaheuristicnonlinear optimization problems
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Abstract (AI)
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.
Key Findings
1
Compared with existing algorithms, the Bat Algorithm obtains optimal solutions that are better than the best previously reported solutions on the tested tasks.
2
The Bat Algorithm is evaluated on eight nonlinear engineering optimization problems from the literature.
3
The algorithm’s formulation and implementation are described in detail, including its distinctive echolocation-inspired search features.
4
The paper analyzes the algorithm’s unique search features and discusses their implications for future optimization research.
5
The paper introduces the Bat Algorithm, a nature-inspired metaheuristic based on bats’ echolocation behavior for global engineering optimization.
Research Object
eight nonlinear engineering optimization problems
Research Subject
the effectiveness and search performance of the bat algorithm for obtaining optimal solutions compared with existing optimization methods
Publication Details
Publication Date
2012-07-13
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