Construction of large-scale global minimum concave quadratic test problems

Bahman Kalantari, J. B. Rosen

Research output: Contribution to journalArticle

14 Citations (Scopus)

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 in Rn+k. The constructed function is strictly concave in the variables x ∈Rn and is linear in the variables y ∈Rk. The number of linear variables k may be much larger than n, so that large-scale global minimization test problems can be constructed by the methods described here.

Original languageEnglish (US)
Pages (from-to)303-313
Number of pages11
JournalJournal of Optimization Theory and Applications
Volume48
Issue number2
DOIs
StatePublished - Feb 1 1986

Fingerprint

Global Minimum
Test Problems
Global Minimization
Constrained Minimization
Concave function
Quadratic Function
Polytope
Global Solution
Minimization Problem
Testing
Strictly
Vertex of a graph

All Science Journal Classification (ASJC) codes

  • Control and Optimization
  • Management Science and Operations Research
  • Applied Mathematics

Keywords

  • Global optimization
  • concave minimization
  • test problems

Cite this

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Construction of large-scale global minimum concave quadratic test problems. / Kalantari, Bahman; Rosen, J. B.

In: Journal of Optimization Theory and Applications, Vol. 48, No. 2, 01.02.1986, p. 303-313.

Research output: Contribution to journalArticle

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