Handling Constraints in Genetic Algorithms Using Dominance-based Tournaments

Abstract

In this paper, we propose a constraint-handling approach for genetic algorithms which uses a dominance-based selection scheme. The proposed approach does not require the fine tuning of a penalty function and does not require extra mechanisms to maintain diversity in the population. The algorithm is validated using several test functions taken from the specialized literature on evolutionary optimization. The results obtained indicate that the approach can produce reasonably good results at low computational costs.