Integrating particle swarm optimization with genetic algorithms for solving nonlinear optimization problems

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...

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Bibliographic Details
Published in:	Journal of computational and applied mathematics Vol. 235; no. 5; pp. 1446 - 1453
Main Authors:	Abd-El-Wahed, W.F., Mousa, A.A., El-Shorbagy, M.A.
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier B.V 2011 Elsevier
Subjects:	Algorithms Calculus of variations and optimal control Constriction factor Evolution Exact sciences and technology Genetic algorithm Genetic algorithms Heuristic Mathematical analysis Mathematical models Mathematics Nonlinear optimization problems Numerical analysis Numerical analysis. Scientific computation Numerical methods in mathematical programming, optimization and calculus of variations Numerical methods in optimization and calculus of variations Optimization Particle swarm optimization Sciences and techniques of general use Constriction factor Genetic algorithm Nonlinear optimization problems Particle swarm optimization Optimization method Nonlinear problems Global solution Experimental result Numerical analysis Applied mathematics Optimal solution Problem solving Variational calculus Mathematical programming
ISSN:	0377-0427, 1879-1778
Online Access:	Get full text
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