An approach to the MOGAS initialization problem using an algorithm based on path relinking

Abstract

This paper describes an approach to the initialization of Multi-Objective Genetic Algorithms (MOGA). The proposed approach inserts in the initial population some solutions that are already in the Pareto optimal front or near it. These are extreme solutions, and a set of conveniently spaced solutions in the Pareto optimal front, obtained by exact algorithms or heuristics over a mono-objective formulation of the problem. To complete the initial population, the algorithm constructs a path connecting these solutions using an algorithm based on PathRelinking. The performance of this boot approach is compared against the random initialization, the insertion of optimal or sub-optimal solutions without the use of the PathRelinking, and some initialization heuristics that are problem-specific. The results of the empirical comparison provide clear evidence that supports the conclusion that the proposed approach is better than the others in terms of overall effectiveness.