Using Comparative Preference Statements in Hypervolume-Based Interactive Multiobjective Optimization

Dimo Brockhoff 1 Youssef Hamadi 2 Souhila Kaci 3
1 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
3 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : The objective functions in multiobjective optimization problems are often non-linear, noisy, or not available in a closed form and evolutionary multiobjective optimization (EMO) algorithms have been shown to be well applicable in this case. Here, our objective is to facilitate interactive decision making by saving function evaluations outside the "interesting" regions of the search space within a hypervolume-based EMO algorithm. We focus on a basic model where the Decision Maker (DM) is always asked to pick the most desirable solution among a set. In addition to the scenario where this solution is chosen directly, we present the alternative to specify preferences via a set of so-called comparative preference statements. Examples on standard test problems show the working principles, the competitiveness, and the drawbacks of the proposed algorithm in comparison with the recent iTDEA algorithm.
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Dimo Brockhoff, Youssef Hamadi, Souhila Kaci. Using Comparative Preference Statements in Hypervolume-Based Interactive Multiobjective Optimization. LION: Learning and Intelligent Optimization, Feb 2014, Gainesville, FL, United States. pp.121-136, ⟨10.1007/978-3-319-09584-4_13⟩. ⟨hal-00935231⟩

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