PAINT: Pareto front interpolation for nonlinear multiobjective optimization. A method called PAINT is introduced for computationally expensive multiobjective optimization problems. The method interpolates between a given set of Pareto optimal outcomes. The interpolation provided by the PAINT method implies a mixed integer linear surrogate problem for the original problem which can be optimized with any interactive method to make decisions concerning the original problem. When the scalarizations of the interactive method used do not introduce nonlinearity to the problem (which is true e.g. for the synchronous NIMBUS method), the scalarizations of the surrogate problem can be optimized with available mixed integer linear solvers. Thus, the use of the interactive method is fast with the surrogate problem even though the problem is computationally expensive. Numerical examples of applying the PAINT method for interpolation are included.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Martin, Benjamin; Goldsztejn, Alexandre; Granvilliers, Laurent; Jermann, Christophe: On continuation methods for non-linear bi-objective optimization: towards a certified interval-based approach (2016)
- Hartikainen, Markus E.; Lovison, Alberto: PAINT-SICon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization (2015)
- Ojalehto, Vesa; Miettinen, Kaisa; Laukkanen, Timo: Implementation aspects of interactive multiobjective optimization for modeling environments: the case of GAMS-NIMBUS (2014)
- Hartikainen, Markus; Miettinen, Kaisa; Wiecek, Margaret M.: PAINT: Pareto front interpolation for nonlinear multiobjective optimization (2012)