GenConstraint: A programming tool for constraint optimization problems

Abstract

This article presents a software used to solve constrained optimization problems with a modified genetic algorithm, which utilizes a series of modified genetic operators to preserve the feasibility of trial solutions and terminates using a stochastic stopping rule. The software is written entirely in ANSI-C++ and the user can prepare the objective function either in C++ or in Fortran. The article presents the genetic algorithm, the incorporated software as well as some experiments on a series of optimization problems. Also, the proposed software was tested on the design of a two-dimensional filter. The results are compared against the results from the algorithm DONLP2. Keywords: Genetic algorithm, Constrained optimization, Stochastic methods