Filter-based genetic algorithm for mixed variable programming

Abdel-Rahman Hedar; Alaa Fahim

doi:10.3934/naco.2011.1.99

Article Contents

2011, Volume 1, Issue 1: 99-116. Doi: 10.3934/naco.2011.1.99

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Filter-based genetic algorithm for mixed variable programming

Abdel-Rahman Hedar^1, and
Alaa Fahim^2,

1.
Dept. of Computer Science, Faculty of Computers and Information, Assiut University, Assiut 71526
2.
Dept. of Mathematics, Faculty of Science, Assiut University, Assiut 71516

Received: October 2010

Revised: November 2010

Published: January 2011

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Abstract

In this paper, Filter Genetic Algorithm (FGA) method is proposed to find the global optimal of the constrained mixed variable programming problem. The considered problem is reformulated to take the form of optimizing two functions, the objective function and the constraint violation function. Then, the filter set methodology [5] is applied within a genetic algorithm framework to solve the reformulated problem. We use pattern search as local search to improve the obtained solutions. Moreover, the gene matrix criteria [10] has been applied to accelerated the search process and to terminate the algorithm. The proposed method FGA is promising compared with some other methods existing in the literature.

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Mathematics Subject Classification: Primary: 90C11, 68T20, 68W20; Secondary: 68T05.

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