Bat Algorithm Inspired Algorithm for Solving Numerical Optimization Problems

Pei Wei Tsai; Jeng Shyang Pan; Bin Yih Liao; Ming Jer Tsai; Vaci Istanda

doi:10.4028/www.scientific.net/AMM.148-149.134

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 148-149Bat Algorithm Inspired Algorithm for Solving...

Bat Algorithm Inspired Algorithm for Solving Numerical Optimization Problems

Abstract:

Inspired by Bat Algorithm, a novel algorithm, which is called Evolved Bat Algorithm (EBA), for solving the numerical optimization problem is proposed based on the framework of the original bat algorithm. By reanalyzing the behavior of bats and considering the general characteristics of whole species of bat, we redefine the corresponding operation to the bats’ behaviors. EBA is a new method in the branch of swarm intelligence for solving numerical optimization problems. In order to analyze the improvement on the accuracy of finding the near best solution and the reduction in the computational cost, three well-known and commonly used test functions in the field of swarm intelligence for testing the accuracy and the performance of the algorithm, are used in the experiments. The experimental results indicate that our proposed method improves at least 99.42% on the accuracy of finding the near best solution and reduces 6.07% in average, simultaneously, on the computational time than the original bat algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 148-149)

Pages:

134-137

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.148-149.134

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Online since:

December 2011

Authors:

Pei Wei Tsai, Jeng Shyang Pan, Bin Yih Liao, Ming Jer Tsai, Vaci Istanda

Keywords:

Bat Algorithm, Bio-Inspired Computing, Evolved Bat Algorithm, Optimization, Swarm Intelligence

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