A Low-Dimensional Semidefinite Relaxation for the Quadratic Assignment Problem

The quadratic assignment problem (QAP) is arguably one of the hardest NP-hard discrete optimization problems. Problems of dimension greater than 25 are still considered to be large scale. Current successful solution techniques use branch-and-bound methods, which rely on obtaining strong and inexpens...

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Veröffentlicht in:	Mathematics of operations research Jg. 34; H. 4; S. 1008 - 1022
Hauptverfasser:	Ding, Yichuan, Wolkowicz, Henry
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Linthicum INFORMS 01.11.2009 Institute for Operations Research and the Management Sciences
Schlagworte:	Analysis Assignment problem Branch & bound algorithms Comparative analysis Eigenvalues interior point methods Interior points large-scale problems Mathematical inequalities Mathematical permutation Mathematical theorems Mathematical vectors Matrices Objective functions quadratic assignment problem Quadratic programming Relaxation methods (Mathematics) semidefinite programming relaxations Studies United States
ISSN:	0364-765X, 1526-5471
Online-Zugang:	Volltext
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