Numerical Algebra, Control and Optimization (NACO)

Filter-based genetic algorithm for mixed variable programming

Pages: 99 - 116, Volume 1, Issue 1, March 2011      doi:10.3934/naco.2011.1.99

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Abdel-Rahman Hedar - Dept. of Computer Science, Faculty of Computers and Information, Assiut University, Assiut 71526, Egypt (email)
Alaa Fahim - Dept. of Mathematics, Faculty of Science, Assiut University, Assiut 71516, Egypt (email)

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.

Keywords:  Genetic algorithm, filter method, mixed variable programming, pattern search, gene matrix.
Mathematics Subject Classification:  Primary: 90C11, 68T20, 68W20; Secondary: 68T05.

Received: October 2010;      Revised: November 2010;      Available Online: February 2011.