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CLC number: TP301.6

On-line Access: 2014-05-06

Received: 2013-04-11

Revision Accepted: 2013-12-06

Crosschecked: 2014-04-11

Cited: 6

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Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.5 P.363-371


FICA: fuzzy imperialist competitive algorithm

Author(s):  Saeid Arish, Ali Amiri, Khadije Noori

Affiliation(s):  Department of Computer Engineering, University of Zanjan, Zanjan, Iran

Corresponding email(s):   saeed.aiproject@gmail.com, a_amiri@znu.ac.ir, kh.noori90@gmail.com

Key Words:  Optimization problem, Imperialist competitive algorithm (ICA), Fuzzy ICA.

Saeid Arish, Ali Amiri, Khadije Noori. FICA: fuzzy imperialist competitive algorithm[J]. Journal of Zhejiang University Science C, 2014, 15(5): 363-371.

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A1 - Saeid Arish
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A1 - Khadije Noori
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1300088

Despite the success of the imperialist competitive algorithm (ICA) in solving optimization problems, it still suffers from frequently falling into local minima and low convergence speed. In this paper, a fuzzy version of this algorithm is proposed to address these issues. In contrast to the standard version of ICA, in the proposed algorithm, powerful countries are chosen as imperialists in each step; according to a fuzzy membership function, other countries become colonies of all the empires. In absorption policy, based on the fuzzy membership function, colonies move toward the resulting vector of all imperialists. In this algorithm, no empire will be eliminated; instead, during the execution of the algorithm, empires move toward one point. Other steps of the algorithm are similar to the standard ICA. In experiments, the proposed algorithm has been used to solve the real world optimization problems presented for IEEE-CEC 2011 evolutionary algorithm competition. Results of experiments confirm the performance of the algorithm.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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