A Modified Preference-Based Hypervolume Indicator for Interactive Evolutionary Multiobjective Optimization Methods

MaoMao Liang, Babooshka Shavazipour, Bhupinder Saini, Michael Emmerich, Kaisa Miettinen

2024

Abstract

Various interactive evolutionary multiobjective optimization methods have been proposed in the literature for problems with multiple, conflicting objective functions. In these methods, a decision maker, who is a domain expert, iteratively provides preference information to guide the solution process while gaining insight into the problem. To compare interactive evolutionary multiobjective optimization methods, a preference-based hypervolume indicator (PHI) has been proposed to quantify the performance of the methods. PHI was the first indicator designed based on some desirable properties of indicators for interactive evolutionary multiobjective optimization methods. However, it has some shortcomings, such as excluding some potentially interesting solutions and being limited to consider a reference point as a type of preference information. In this paper, a modified indicator called PHI+ is proposed to address the mentioned drawbacks. PHI+ modifies the region of interest in PHI. While PHI is directed at methods where a decision maker provides preference information in the form of a reference point, PHI+ is applicable for methods that utilize desirable ranges of objective function values as preference information. Therefore, PHI+ is the first indicator that can handle preference information provided as desirable ranges when evaluating interactive methods. Experimental results show that PHI+ can also better distinguish differences in the performance of interactive evolutionary multiobjective optimization methods.

Paper Citation

in Harvard Style

Liang M., Shavazipour B., Saini B., Emmerich M. and Miettinen K. (2024). A Modified Preference-Based Hypervolume Indicator for Interactive Evolutionary Multiobjective Optimization Methods. In Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA; ISBN 978-989-758-721-4, SciTePress, pages 214-221. DOI: 10.5220/0012934600003837

in Bibtex Style

@conference{ecta24,
author={MaoMao Liang and Babooshka Shavazipour and Bhupinder Saini and Michael Emmerich and Kaisa Miettinen},
title={A Modified Preference-Based Hypervolume Indicator for Interactive Evolutionary Multiobjective Optimization Methods},
booktitle={Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA},
year={2024},
pages={214-221},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012934600003837},
isbn={978-989-758-721-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA
TI - A Modified Preference-Based Hypervolume Indicator for Interactive Evolutionary Multiobjective Optimization Methods
SN - 978-989-758-721-4
AU - Liang M.
AU - Shavazipour B.
AU - Saini B.
AU - Emmerich M.
AU - Miettinen K.
PY - 2024
SP - 214
EP - 221
DO - 10.5220/0012934600003837
PB - SciTePress