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Quadratic Optimization Models and Convex Extensions on Permutation Matrix Set

  • Oksana PichuginaEmail author
  • Sergiy Yakovlev
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1080)

Abstract

A new approach to the construction of lower bounds of quadratic function the permutation matrix set, based on the utilization of functional representations and convex extensions, is offered. Several quadratic functional representations of the are formed. A family of one-parametric convex quadratic extensions of a quadratic function from the set onto the Euclidean space is formed. The results can be applied in approximate and exact methods of quadratic optimization on the permutation matrix set.

Keywords

Permutation matrix set Euclidean combinatorial set Unconstrained quadratic optimization Convex extension Continuous functional representation 

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Copyright information

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Authors and Affiliations

  1. 1.National Aerospace University “Kharkiv Aviation Institute”KharkivUkraine

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