PAINT-SiCon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization
Hartikainen, M., & Lovison, A. (2015). PAINT-SiCon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization. Journal of Global Optimization, 62(2), 243-261. https://doi.org/10.1007/s10898-014-0232-9
Published inJournal of Global Optimization
© Springer Science+Business Media New York 2014. This is a final draft version of an article whose final and definitive form has been published by Springer. Published in this repository with the kind permission of the publisher.
We introduce a novel approximation method for multiobjective optimization problems called PAINT–SiCon. The method can construct consistent parametric representations of Pareto sets, especially for nonconvex problems, by interpolating between nondominated solutions of a given sampling both in the decision and objective space. The proposed method is especially advantageous in computationally expensive cases, since the parametric representation of the Pareto set can be used as an inexpensive surrogate for the original problem during the decision making process.
PublisherSpringer New York LLC
ISSN Search the Publication Forum0925-5001
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