Demonstrating the Applicability of PAINT to Computationally Expensive Real-life Multiobjective Optimization
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 int...
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Main Authors | , |
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Format | Journal Article |
Language | English |
Published |
15.09.2011
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Subjects | |
Online Access | Get full text |
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Summary: | 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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DOI: | 10.48550/arxiv.1109.3411 |