An elitist genetic algorithm for multiobjective optimization

Abstract

Solving multiobjective engineering problems is, in general, a difficult task. In spite of the success of many approaches, elitism has emerged has an effective way of improving the performance of algorithms. In this paper, a new elitist scheme, by which it is possible to control the size of the elite population, as well as the concentration of points in the approximation to the Pareto-optimal set, is introduced. This new scheme is tested on several multiobjective problems and, it proves to lead to a good compromise between computational time and size of the elite population.