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Improved chemotaxis differential evolution optimization algorithm


Yıldız, Y. Emre and Altun, Oğuz and Topal, A. Osman (2015) Improved chemotaxis differential evolution optimization algorithm. In: 5th International Conference on Computing and Informatics (ICOCI) 2015, 11-13 August 2015, Istanbul, Turkey.

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Abstract

The social foraging behavior of Escherichia coli has recently received great attention and it has been employed to solve complex search optimization problems.This paper presents a modified bacterial foraging optimization BFO algorithm, ICDEOA (Improved Chemotaxis Differential Evolution Optimization Algorithm), to cope with premature convergence of reproduction operator.In ICDEOA, reproduction operator of BFOA is replaced with probabilistic reposition operator to enhance the intensification and the diversification of the search space.ICDEOA was compared with state-of-the-art DE and non-DE variants on 7 numerical functions of the 2014 Congress on Evolutionary Computation (CEC 2014). Simulation results of CEC 2014 benchmark functions reveal that ICDEOA performs better than that of competitors in terms of the quality of the final solution for high dimensional problems.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN No: 978-967-0910-02-4 Jointly organized by : Universiti Utara Malaysia & Istanbul Zaim University
Uncontrolled Keywords: bacterial foraging optimization algorithm (BFOA), differential evolution (DE), computational chemotaxis, hybrid optimization, improved chemotaxis differential evolution optimization algorithm (ICDEOA)
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Computing
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 01 Oct 2015 06:17
Last Modified: 28 Apr 2016 01:59
URI: http://repo.uum.edu.my/id/eprint/15573

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