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Nature-inspired algorithms are among the most powerful algorithms foroptimization. In this study, a new nature-inspired metaheuristic optimizationalgorithm, called bat algorithm (BA), is introduced for solving engineeringoptimization tasks. The proposed BA is based on the echolocation behavior ofbats. After a detailed formulation and explanation of its implementation, BA isverified using eight nonlinear engineering optimization problems reported inthe specialized literature. BA has been carefully implemented and carried outoptimization for eight well-known optimization tasks. Then, a comparison hasbeen made between the proposed algorithm and other existing algorithms. Theoptimal solutions obtained by the proposed algorithm are better than the bestsolutions obtained by the existing methods. The unique search features used inBA are analyzed, and their implications for future research are also discussedin detail.

Bat Algorithm: A Novel Approach for Global Engineering Optimization