Title: Fuzzy brain storming optimisation algorithm

Authors: Rabie A. Ramadan

Addresses: Department of Computer Engineering, Cairo University, Cairo, Egypt; Hail University, Hail, Kingdom of Saudi Arabia

Abstract: Recently, brain storming optimisation (BSO) is proposed to solve some of the optimisation problems. The original version of BSO ignores the concept of sharing the same idea among different groups. In addition, since BSO focuses on the cluster centres and gives them the highest priority, it might fall into local optima. Therefore, this paper proposes a modified BSO algorithm entitled fuzzy brain storing optimisation (FBSO) that tries to solve these two problems by: 1) sharing the same idea with different groups using fuzzy C-mean instead of K-mean; 2) the paper uses a predator-prey approach when generating new ideas to deviate the search from the local optima; 3) testing the BSO and FBSO on one of the important problems in wireless sensor networks (WSNs) which is the energy topology control (ETC) problem. The results of FBSO seem promising and outperform the BSO in many cases.

Keywords: brain storming optimisation; BSO; fuzzy C-means clustering; FCM clustering; wireless sensor networks; WSNs; optimisation; predator-prey approach; energy topology control; ETC.

DOI: 10.1504/IJIEI.2017.082568

International Journal of Intelligent Engineering Informatics, 2017 Vol.5 No.1, pp.67 - 79

Received: 25 Jan 2016
Accepted: 25 Feb 2016

Published online: 01 Mar 2017 *

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