DocumentCode :
1326463
Title :
Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions
Author :
Wagner, Tobias ; Trautmann, Heike
Author_Institution :
Inst. of Machining Technol., Tech. Univ. Dortmund, Dortmund, Germany
Volume :
14
Issue :
5
fYear :
2010
Firstpage :
688
Lastpage :
701
Abstract :
In this paper, a concept for efficiently approximating the practically relevant regions of the Pareto front (PF) is introduced. Instead of the original objectives, desirability functions (DFs) of the objectives are optimized, which express the preferences of the decision maker. The original problem formulation and the optimization algorithm do not have to be modified. DFs map an objective to the domain [0, 1] and nonlinearly increase with better objective quality. By means of this mapping, values of different objectives and units become comparable. A biased distribution of the solutions in the PF approximation based on different scalings of the objectives is prevented. Thus, we propose the integration of DFs into the S-metric selection evolutionary multiobjective algorithm. The transformation ensures the meaning of the hypervolumes internally computed. Furthermore, it is shown that the reference point for the hypervolume calculation can be set intuitively. The approach is analyzed using standard test problems. Moreover, a practical validation by means of the optimization of a turning process is performed.
Keywords :
Pareto optimisation; decision making; evolutionary computation; turning (machining); PF approximation; Pareto front; S-metric selection evolutionary multiobjective algorithm; decision maker; desirability function; hypervolume-based multiobjective evolutionary algorithms; optimization algorithm; problem formulation; turning process; Approximation algorithms; Approximation methods; Delta modulation; Evolutionary computation; Indexes; Optimization; Shape; Desirability function; SMS-EMOA; hypervolume indicator; preferences;
fLanguage :
English
Journal_Title :
Evolutionary Computation, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-778X
Type :
jour
DOI :
10.1109/TEVC.2010.2058119
Filename :
5575414
Link To Document :
بازگشت