6533b826fe1ef96bd12847a7

RESEARCH PRODUCT

PAINT–SiCon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization

Alberto LovisonMarkus Hartikainen

subject

Mathematical optimizationControl and OptimizationApplied MathematicsMathematicsofComputing_NUMERICALANALYSISPareto principleSampling (statistics)Management Science and Operations ResearchSpace (mathematics)Multi-objective optimizationComputer Science ApplicationsNonlinear programmingSet (abstract data type)piecewise linear approximationmultiple criteria programmingnonlinear programmingRepresentation (mathematics)Parametric statisticsMathematics

description

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. peerReviewed

yearjournalcountryeditionlanguage
2014-08-21Journal of Global Optimization
https://doi.org/10.1007/s10898-014-0232-9