DocumentCode
1477626
Title
The r-Dominance: A New Dominance Relation for Interactive Evolutionary Multicriteria Decision Making
Author
Ben Said, Lamjed ; Bechikh, Slim ; Ghédira, Khaled
Author_Institution
Intell. Inf. Eng. Lab. (LI3), Univ. of Tunis, Tunis, Tunisia
Volume
14
Issue
5
fYear
2010
Firstpage
801
Lastpage
818
Abstract
Evolutionary multiobjective optimization (EMO) methodologies have gained popularity in finding a representative set of Pareto optimal solutions in the past decade and beyond. Several techniques have been proposed in the specialized literature to ensure good convergence and diversity of the obtained solutions. However, in real world applications, the decision maker is not interested in the overall Pareto optimal front since the final decision is a unique solution. Recently, there has been an increased emphasis in addressing the decision-making task in searching for the most preferred alternatives. In this paper, we introduce a new variant of the Pareto dominance relation, called r-dominance, which has the ability to create a strict partial order among Pareto-equivalent solutions. This fact makes such a relation able to guide the search toward the interesting parts of the Pareto optimal region based on the decision maker´s preferences expressed as a set of aspiration levels. After integrating the new dominance relation in the NSGA-II methodology, the efficacy and the usefulness of the modified procedure are assessed through two to ten-objective test problems a priori and interactively. Moreover, the proposed approach provides competitive and better results when compared to other recently proposed preference-based EMO approaches.
Keywords
Pareto optimisation; decision making; evolutionary computation; interactive systems; EMO approach; NSGA-II methodology; Pareto dominance relation; Pareto optimal region; Pareto optimal solutions; Pareto-equivalent solutions; evolutionary multiobjective optimization methodology; interactive evolutionary multicriteria decision making; r-dominance; Constraint optimization; Decision making; Delta modulation; Engineering management; Evolutionary computation; Operations research; Pareto optimization; Shape; Sorting; Testing; Decision maker´s preferences; Pareto dominance; evolutionary algorithms; interactive multiobjective optimization; reference point method;
fLanguage
English
Journal_Title
Evolutionary Computation, IEEE Transactions on
Publisher
ieee
ISSN
1089-778X
Type
jour
DOI
10.1109/TEVC.2010.2041060
Filename
5453088
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