A MODIFIED BAT ALGORITHM FOR SOLVING GLOBAL OPTIMIZATION PROBLEM

N. O. Krasnoshlyk

Abstract


In this paper we consider a bat algorithm for solving the problem of global optimization. This metaheuristic algorithm applies to swarm intelligence algorithms, which are developing rapidly in recent years. The aim of the work is to improve the bat algorithm, study its efficiency and application for solving optimization problems. A modified version of the algorithm in which to calculate speed of the bats used the technique of particle swarm optimization is proposed. The computational experiments have been conducted to compare the accuracy and the speed of convergence of the canonical and the modified algorithms. It was found that the proposed version of the algorithm is more effective in finding the global minimum of unimodal and multimodal test functions. The dependence of the efficiency of modified bat algorithm from the set parameters is investigated. As variable parameters chosen initial values of the loudness and pulse emission rate emitted by bats. The modified algorithm is applied to solve practical problem of minimize the cost of pressure vessel design. The comparison of the solution of the optimization problem with the results of other authors who used both classical and population algorithms was conducted.

Keywords


bat algorithm, population algorithm, swarm intelligence, global optimization.

References


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DOI: http://dx.doi.org/10.15588/1607-3274-2015-4-14



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