Abstract
Due to the big success of the Pareto’s Optimality Criteria for multi–objective problems, an increasing number of algorithms that use it have been proposed. The goal of these algorithms is to find a set of non–dominated solutions that are close to the True Pareto front. As a consequence, a new problem has arisen, how can the performance of different algorithms be evaluated? In this paper, we present a novel system to evaluate m non–dominated sets, based on a few assumptions about the preferences of the decision maker. In order to evaluate the performance of our approach, we build several test cases considering different topologies of the Pareto front. The results are compared with those of another popular metric, the S–metric, showing equal or better performance.
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Lizárraga, G., Hernández, A., Botello, S. (2007). G–Indicator: An M–Ary Quality Indicator for the Evaluation of Non–dominated Sets. In: Gelbukh, A., Kuri Morales, Á.F. (eds) MICAI 2007: Advances in Artificial Intelligence. MICAI 2007. Lecture Notes in Computer Science(), vol 4827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76631-5_12
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DOI: https://doi.org/10.1007/978-3-540-76631-5_12
Publisher Name: Springer, Berlin, Heidelberg
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