Construction of large-scale global minimum concave quadratic test problems |
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Authors: | B Kalantari J B Rosen |
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Institution: | (1) Department of Computer Science, Rutgers University, New Brunswick, New Jersey;(2) Computer Science Department, University of Minnesota, Minneapolis, Minnesota |
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Abstract: | Construction of problems with known global solutions is important for the computational testing of constrained global minimization algorithms. In this paper, it is shown how to construct a concave quadratic function which attains its global minimum at a specified vertex of a polytope inR
n+k. The constructed function is strictly concave in the variablesx R
n and is linear in the variablesy R
k. The number of linear variablesk may be much larger thann, so that large-scale global minimization test problems can be constructed by the methods described here.This research was supported by the Computer Science Section of the National Science Foundation under Grant No. MCS-81-01214. |
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Keywords: | Global optimization test problems concave minimization |
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