IMPROVING THE PERFORMANCE OF TRAJECTORY-BASED MULTIOBJECTIVE OPTIMISERS BY USING RELAXED DOMINANCE

Several recent proposed techniques for multiobjective optimisation use the dominance relation to establish preference among solutions. In this paper, the Pareto archived evolutionary strategy and a population-based annealing algorithm are applied to test instances of a highly constrained combinatorial optimisation problem: academic space allocation. It is shown that the performance of both algorithms is improved by using a relaxed dominance relation and it appears that there is a correlation between this and the existence of constraints in the problem. This paper also discusses why more flexible selection methods may produce better results than the dominance relation in some algorithms and some problem domains.

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