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A Comprehensive Analysis of the Bat Algorithm

  • Yury Zorin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 754)

Abstract

Optimization is one of the most challenging problems that has received considerable attention over the last decade. The bio-inspired evolutionary optimization algorithms due to their robustness, simplicity and efficiency are widely used to solve complex optimization problems. The Bat algorithm is one of the most recent one from this category. Given that the original Bat algorithm is vulnerable to local optimum and unsatisfactory calculation accuracy, the paper presents detailed analysis of its main stages and a measure of their influence on the algorithm performance. In particular, the global best solution acceptance condition, the way a new solution is generated by random flight and the local search procedure implementation have been studied. The ways to overcome the original algorithm’s flaws have been suggested. Their effectiveness has been proved by numerous computational experiments.

Keywords

Optimization problem Metaheuristic algorithm Bat algorithm Lévy flight 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.National Technical University of Ukraine ‘‘Igor Sikorsky Kyiv Polytechnic Institute’’KyivUkraine

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