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Title: Fuzzy brain storming optimisation algorithm
Author: Rabie A. Ramadan
Address: 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.
Int. J. of Intelligent Engineering Informatics, 2017 Vol.5, No.1, pp.67 - 79
Submission date: 09 Jan 2016
Date of acceptance: 25 Feb 2016
Available online: 23 Feb 2017