Authors:
MaoMao Liang
;
Babooshka Shavazipour
;
Bhupinder Saini
;
Michael Emmerich
and
Kaisa Miettinen
Affiliation:
University of Jyvaskyla, Faculty of Information Technology, P.O. Box 35 (Agora), 40014 University of Jyvaskyla, Finland
Keyword(s):
Multiple Objective Optimization, Interactive Methods, Performance Indicators, Region of Interest, Evolutionary Algorithms, Preference-Based Hypervolume.
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.
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