Journal of Computer and Communications, 2014, 2, 137-141

Published Online March 2014 in SciRes. http://www.scirp.org/journal/jcc

http://dx.doi.org/10.4236/jcc.2014.24018

How to cite this paper: Iscan, H. and Gunduz, M. (2014) Parameter Analysis on Fruit Fly Optimization Algorithm. Journal of

Computer and Communications, 2, 137-141. h ttp://dx. doi.org/10. 4236/j cc.2014.2 4018

Parameter Analysis on Fruit Fly

Optimization Algorithm

Hazim Iscan, Mesut Gunduz

Computer Engineering Department, Selçuk University, Konya, Turkey

Email: iscan@selcu k.edu.tr, mgunduz@selcuk.edu.tr

Received Novemb er 2013

Abstract

Fruit fly algorithm is a novel intelligent optimization algorithm based on foraging behavior of the

real fruit flies. In order to find optimum solution for an optimization problem, fixed parameters

are obtained as a result of manual test in fruit fly algorithm. In this study, it is aimed to find the

optimum solution by analyzing the constant parameter concerning the direction of the algorithm

instead of manual defining on initialization stage. The study shows an automated approach for

finding the related parameter by utilizing grid search algorithm. According to the experimental

results, it can be seen that this approach could be used as an alternative way for finding related

parameter or other ones in order to achieve optimum model.

Keywords

Fruit Fly; Optimization

1. Introduction

Intelligent optimization algorithms are attracting the attention of many scholars in recent years. These algo-

rithms with their simple steps and efficient search methods have become the most widely used in optimization

problems which require performance. Particle swarm optimization (PSO) [1,2], ant colony optimization (ACO)

[3], artificial bee colony algorithm (ABC) [4], Simulated Annealing (SA) algorithm [5], Bacterial Colony Che-

motaxis (BCC) [6] and Fruit Fly Optimization algorithm (FOA) [7,8] are some of them. Fruit fly algorithm re-

cently joined the intelligent optimization algorithms group. This algorithm is introduced by Wen Tsao Pan in

2011. The algorithm is originated from foraging behavior of fruit flies. The algorithm can be easily understand-

able because of its simple structure. Its updating strategy, which used to find best solution, is simpler than other

algorithms. However, manually definition of this update strategy causes a disadvantage. A method has been

tried to develop for eliminatin g this disadvantage and improving performance of algorithm. In this method, the

manually defined parameters of algorithm, defined with the help of search algorithm. With this new method the

functions which tested in Fruit fly algorithm have been used and obtained better results.

2. Fruit Fly Optimization Algorithm

Fruit fly optimization algorithm is the latest evolutionary computation technique which was pointed out by Wen