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Growing Science » Decision Science Letters » A hybrid of genetic algorithm and Fletcher-Reeves for bound constrained optimization problems

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Decision Science Letters

ISSN 1929-5812 (Online) - ISSN 1929-5804 (Print)
Quarterly Publication
Volume 4 Issue 2 pp. 125-136 , 2015

A hybrid of genetic algorithm and Fletcher-Reeves for bound constrained optimization problems Pages 125-136 Right click to download the paper Download PDF

Authors: Asoke Kumar Bhunia, Pintu Pal, Samiran Chattopadhyay

DOI: 10.5267/j.dsl.2015.1.003

Keywords: Bound Constrained Optimization problem, Fletcher Reeves method, Genetic Algorithm, Global-optima, Hybrid Algorithm

Abstract: In this paper a hybrid algorithm for solving bound constrained optimization problems having continuously differentiable objective functions using Fletcher Reeves method and advanced Genetic Algorithm (GA) have been proposed. In this approach, GA with advanced operators has been applied for computing the step length in the feasible direction in each iteration of Fletcher Reeves method. Then this idea has been extended to a set of multi-point approximations instead of single point approximation to avoid the convergence of the existing method at local optimum and a new method, called population based Fletcher Reeves method, has been proposed to find the global or nearer to global optimum. Finally to study the performance of the proposed method, several multi-dimensional standard test functions having continuous partial derivatives have been solved. The results have been compared with the same of recently developed hybrid algorithm with respect to different comparative factors.

How to cite this paper
Bhunia, A., Pal, P & Chattopadhyay, S. (2015). A hybrid of genetic algorithm and Fletcher-Reeves for bound constrained optimization problems.Decision Science Letters , 4(2), 125-136.

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Journal: Decision Science Letters | Year: 2015 | Volume: 4 | Issue: 2 | Views: 2418 | Reviews: 0

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