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Integrating Preference by Means of Desirability Function with Evolutionary Multi-objective Optimization


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Abstract

Desirability function is a mathematically simple description of decision maker0027s preference. A desirability function transforms objective function to a scale-free desirability value, which actually measures the decision maker0027s satisfaction with the objective value. In this paper, we utilize desirability functions to express decision maker0027s preference to specific regions with an objective. These desirability functions are integrated into evolutionary multi-objective algorithms to generate a uniformly distributed set of Pareto solutions in desirability space. The corresponding images in objective space of this set of solutions are exactly the decision maker0027s preferred solutions. The experimental results show the effectiveness of this approach.


Keywords


Pages

Total Pages: 13
Pages: 197-209

DOI
10.1080/10798587.2014.961313


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Published

Volume: 21
Issue: 2
Year: 2014

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JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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