PAINT: Pareto front interpolation for nonlinear multiobjective optimization

Abstract
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.
Main Authors
Format
Articles Research article
Published
2012
Series
Subjects
Publication in research information system
Publisher
Springer
Original source
http://www.springerlink.com/content/x8548782129x3832/?MUD=MP
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201607283684Use this for linking
Review status
Peer reviewed
ISSN
0926-6003
DOI
https://doi.org/10.1007/s10589-011-9441-z
Language
English
Published in
Computational Optimization and Applications
Citation
  • Hartikainen, M., Miettinen, K., & Wiecek, M. M. (2012). PAINT: Pareto front interpolation for nonlinear multiobjective optimization. Computational Optimization and Applications, 52(3), 845-867. https://doi.org/10.1007/s10589-011-9441-z
License
Open Access
Copyright© Springer International Publishing AG

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