Demonstrating the Applicability of PAINT to Computationally Expensive Real-life Multiobjective Optimization

Abstract

We demonstrate the applicability of a new PAINT method to speed up iterations of interactive methods in multiobjective optimization. As our test case, we solve a computationally expensive non-linear, five-objective problem of designing and operating a wastewater treatment plant. The PAINT method interpolates between a given set of Pareto optimal outcomes and constructs a computationally inexpensive mixed integer linear surrogate problem for the original problem. We develop an IND-NIMBUS R © PAINT module to combine the interactive NIMBUS method and the PAINT method and to find a preferred solution to the original problem. With the PAINT method, the solution process with the NIMBUS method take a comparatively short time even though the original problem is computationally expensive.

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Cite this paper

@article{Hartikainen2011DemonstratingTA, title={Demonstrating the Applicability of PAINT to Computationally Expensive Real-life Multiobjective Optimization}, author={Markus Hartikainen and Vesa Ojalehto}, journal={CoRR}, year={2011}, volume={abs/1109.3411} }