Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities
S. Mostaghim, H. Trautmann, O. Mersmann, in: R. Schaefer, C. Cotta, J. Kołodziej, G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI, Springer Berlin Heidelberg, Berlin, Heidelberg, 2010, pp. 101–110.
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Conference Paper
| English
Author
Mostaghim, Sanaz;
Trautmann, HeikeLibreCat 
;
Mersmann, Olaf
;
Mersmann, OlafEditor
Schaefer, Robert;
Cotta, Carlos;
Kołodziej, Joanna;
Rudolph, Günter
Abstract
The integration of experts’ preferences is an important aspect in multi-objective optimization. Usually, one out of a set of Pareto optimal solutions has to be chosen based on expert knowledge. A combination of multi-objective particle swarm optimization (MOPSO) with the desirability concept is introduced to efficiently focus on desired and relevant regions of the true Pareto front of the optimization problem which facilitates the solution selection process. Desirability functions of the objectives are optimized, and the desirability index is used for selecting the global best particle in each iteration. The resulting MOPSO variant DF-MOPSO in most cases exclusively generates solutions in the desired area of the Pareto front. Approximations of the whole Pareto front result in cases of misspecified desired regions.
Publishing Year
Proceedings Title
Parallel Problem Solving from Nature, PPSN XI
Page
101–110
ISBN
LibreCat-ID
Cite this
Mostaghim S, Trautmann H, Mersmann O. Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities. In: Schaefer R, Cotta C, Kołodziej J, Rudolph G, eds. Parallel Problem Solving from Nature, PPSN XI. Springer Berlin Heidelberg; 2010:101–110. doi:https://doi.org/10.1007/978-3-642-15871-1_11
Mostaghim, S., Trautmann, H., & Mersmann, O. (2010). Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities. In R. Schaefer, C. Cotta, J. Kołodziej, & G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI (pp. 101–110). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_11
@inproceedings{Mostaghim_Trautmann_Mersmann_2010, place={Berlin, Heidelberg}, title={Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities}, DOI={https://doi.org/10.1007/978-3-642-15871-1_11}, booktitle={Parallel Problem Solving from Nature, PPSN XI}, publisher={Springer Berlin Heidelberg}, author={Mostaghim, Sanaz and Trautmann, Heike and Mersmann, Olaf}, editor={Schaefer, Robert and Cotta, Carlos and Kołodziej, Joanna and Rudolph, Günter}, year={2010}, pages={101–110} }
Mostaghim, Sanaz, Heike Trautmann, and Olaf Mersmann. “Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities.” In Parallel Problem Solving from Nature, PPSN XI, edited by Robert Schaefer, Carlos Cotta, Joanna Kołodziej, and Günter Rudolph, 101–110. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. https://doi.org/10.1007/978-3-642-15871-1_11.
S. Mostaghim, H. Trautmann, and O. Mersmann, “Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities,” in Parallel Problem Solving from Nature, PPSN XI, 2010, pp. 101–110, doi: https://doi.org/10.1007/978-3-642-15871-1_11.
Mostaghim, Sanaz, et al. “Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities.” Parallel Problem Solving from Nature, PPSN XI, edited by Robert Schaefer et al., Springer Berlin Heidelberg, 2010, pp. 101–110, doi:https://doi.org/10.1007/978-3-642-15871-1_11.
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