Adopting dynamic operators in a genetic algorithm

Authors:
Khadiza Tahera;Raafat N. Ibrahim;Paul B. Lochert
Affiliations:
Monash University, Melbourne, Australia;Monash University, Melbourne, Australia;Monash University, Melbourne, Australia
Venue:
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Year:
2007

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Abstract

Genetic Algorithms have been used to solve difficult optimization problems in a number of fields. However, in order to solve a problem with GA, the user has to specify a number of parameters.allThis parameter tuning is a difficult task as different genetic operators are suitable in different application areas. This paper proposes a scheme for genetic algorithms where the genetic operators are changed randomly. The information of gender and age is also incorporated in this approach to maintain population diversity. The experimental result of the proposed algorithm based on a mechanical design problem shows promising result.