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



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.



Total Pages: 13
Pages: 197-209


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Volume: 21
Issue: 2
Year: 2014

Cite this document


Coello, C., Lamont, G. & Veldhuizen, D. V. (2007). Evolutionary algorithms for solving multiobjective problem (2nd ed.). Springer, 31–32.

Deb, K. et al. "A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II." IEEE Transactions on Evolutionary Computation 6.2 (2002): 182-197. Crossref. Web.

Zitzler, E., Laumanns, M. & Thiele, L. (2001). SPEA2: Improving the strength pareto evolutionary algorithm for multiobjective optimization. in Evolutionary Methods for Design Optimization and Control with Applications to Industrial Problems, K. C. Giannakoglou, D. T. Tsahalis, J. P”eriaux, K. D. Papailiou, and T. Fogarty, Eds.Athens: Greece, pp. 95–100.

Qingfu Zhang, and Hui Li. "MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition." IEEE Transactions on Evolutionary Computation 11.6 (2007): 712-731. Crossref. Web.

Liu, Hai-Lin, Yuping Wang, and Yiu-Ming Cheung. "A Multi-Objective Evolutionary Algorithm Using Min-Max Strategy And Sphere Coordinate Transformation." Intelligent Automation & Soft Computing 15.3 (2009): 361-384. Crossref. Web.

Zitzler E. Lecture Notes on Computer Science

Beume, Nicola, Boris Naujoks, and Michael Emmerich. "SMS-EMOA: Multiobjective Selection Based on Dominated Hypervolume." European Journal of Operational Research 181.3 (2007): 1653-1669. Crossref. Web.

Branke, Jürgen et al. "Interactive Evolutionary Multiobjective Optimization Using Robust Ordinal Regression." Evolutionary Multi-Criterion Optimization (2009): 554-568. Crossref. Web.

Cvetkovic, D., and I.C. Parmee. "Preferences and Their Application in Evolutionary Multiobjective Optimization." IEEE Transactions on Evolutionary Computation 6.1 (2002): 42-57. Crossref. Web.

Kim, Jong-Hwan et al. "Preference-Based Solution Selection Algorithm for Evolutionary Multiobjective Optimization." IEEE Transactions on Evolutionary Computation 16.1 (2012): 20-34. Crossref. Web.

Reference point based multi-objective optimization using evolutionary algorithms

Mohammadi A. IEEE World Congress on Computational Inteliigence

Wierzbicki, A. P., The use of reference objectives in multiobjective optimization. In G.Fandel & T.Gal (Eds.), Multiple Criteria Decision Making Theory and Applications (pp. 468–486). Berlin: Springer-Verlag.

Thiele, Lothar et al. "A Preference-Based Evolutionary Algorithm for Multi-Objective Optimization." Evolutionary Computation 17.3 (2009): 411-436. Crossref. Web.

Wagner, Tobias, and Heike Trautmann. "Integration of Preferences in Hypervolume-Based Multiobjective Evolutionary Algorithms by Means of Desirability Functions." IEEE Transactions on Evolutionary Computation 14.5 (2010): 688-701. Crossref. Web.

Li Zhenhua Proceedings International Conference on Computational Intelligence and Security

K. (1999). Miettinen, nonlinear multi-objective optimization. Kluwer Academic Publishers.

Derringer G. Journal of Quality Technology

Harington J. Industrial Quality Control

Deb, K. (2001). Multi-objective optimization using evolutionary algorithm. England: John Wiley Sons.


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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