Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/100854
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Type: Journal article
Title: Distribution network reconfiguration based on parallel genetic membrane computing
Author: Lei, X.
Wu, H.
Shi, Y.
Shi, P.
Citation: Journal of Intelligent & Fuzzy Systems, 2015; 29(5):2287-2298
Publisher: IOS Press
Issue Date: 2015
ISSN: 1064-1246
1875-8967
Statement of
Responsibility: 
Xia Lei, Hongjian Wu, Yan Shi and Peng Shi
Abstract: As a new branch of natural computing, membrane computing (MC) has become a hot topic. Based on the combination of nested structure membrane optimization method, genetic algorithm (GA) and the distributed computing method, an efficient parallel genetic membrane computing (PGMC) is proposed. Some rules are proposed to improve the computational performance of PGMC such as communication and transportation rules between homo-core membranes and hetero-core membranes, elementary membrane crossover and division rules, mutation and dissolving rules. An application of PGMC to distribution network reconfiguration is presented. According to the features of radial distribution network operation, object generation of minimum loop and equal selection of crossover probability are used to further improve the computational efficiency. Finally, a typical example of 33-nodes net is simulated by comparing PGMC with general GA and genetic membrane computing (GMC). The results demonstrate superiority of PGMC on convergence, stability, global searching ability and so on.
Keywords: Membrane computing; distributed computing method; parallel genetic membrane computing; network reconfiguration; minimum loop
Rights: © 2015 – IOS Press and the authors. All rights reserved
RMID: 0030040557
DOI: 10.3233/IFS-151704
Grant ID: http://purl.org/au-research/grants/arc/DP140102180
http://purl.org/au-research/grants/arc/LP140100471
Appears in Collections:Electrical and Electronic Engineering publications

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