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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
mathematics
Integrating particle swarm optimization with genetic algorithms for solving nonlinear optimization problems
Journal of Computational and Applied Mathematics, Volume 235, No. 5, Year 2011
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Description
Heuristic optimization provides a robust and efficient approach for solving complex real-world problems. The aim of this paper is to introduce a hybrid approach combining two heuristic optimization techniques, particle swarm optimization (PSO) and genetic algorithms (GA). Our approach integrates the merits of both GA and PSO and it has two characteristic features. Firstly, the algorithm is initialized by a set of random particles which travel through the search space. During this travel an evolution of these particles is performed by integrating PSO and GA. Secondly, to restrict velocity of the particles and control it, we introduce a modified constriction factor. Finally, the results of various experimental studies using a suite of multimodal test functions taken from the literature have demonstrated the superiority of the proposed approach to finding the global optimal solution. © 2010 Elsevier B.V. All rights reserved.
Authors & Co-Authors
Abd El-Wahed, Waiel F.
Egypt, Shibin el Kom
Menoufia University
Mousa, Abd Allah A.
Egypt, Shibin el Kom
Faculty of Engineering
El-Shorbagy, M. A.
Egypt, Shibin el Kom
Faculty of Engineering
Statistics
Citations: 141
Authors: 3
Affiliations: 2
Identifiers
Doi:
10.1016/j.cam.2010.08.030
ISSN:
03770427
Research Areas
Genetics And Genomics