Combining Simple and Adaptive Monte Carlo Methods for Approximating Hypervolume

Published: 01 Jan 2020, Last Modified: 07 May 2024IEEE Trans. Evol. Comput. 2020EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: The computation of hypervolume is a key issue in multiobjective optimization, particularly, multiobjective evolutionary optimization. However, it is NP-hard to compute the exact hypervolume value. Monte Carlo methods have been widely used for approximating the hypervolume. Observing that the basic Monte Carlo method and the fully polynomial-time randomized approximation scheme (FPRAS) suit different solution sets, we propose a combination of these two methods and show that it performs very well on a number of solution sets.
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