Exploiting group symmetry in semidefinite programming relaxations of the quadratic assignment problem

We consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: (Burkard et al. i...

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Vydané v:Mathematical programming Ročník 122; číslo 2; s. 225 - 246
Hlavní autori: de Klerk, Etienne, Sotirov, Renata
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer-Verlag 01.04.2010
Springer
Springer Nature B.V
Predmet:
Applied sciences
Assignment problem
Calculus of Variations and Optimal Control; Optimization
Combinatorics
Exact sciences and technology
Full Length Paper
Libraries
Logistics
Mathematical and Computational Physics
Mathematical Methods in Physics
Mathematical programming
Mathematics
Mathematics and Statistics
Mathematics of Computing
Numerical Analysis
Operational research and scientific management
Operational research. Management science
Quadratic programming
Sparsity
Studies
Symmetry
Theoretical
Traveling salesman problem
70-08
Semidefinite programming
20Cxx
Quadratic assignment problem
Group symmetry
90C22
Lower bound
Semidefinite relaxation
Assignment problem
Semi definite programming
Quadratic assignment
Quadratic programming
Location problem
Symmetry group
Mathematical programming
ISSN:0025-5610, 1436-4646
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Popis
Shrnutí:We consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: (Burkard et al. in J Global Optim 10:291–403, 1997).
Bibliografia:SourceType-Scholarly Journals-1
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ISSN:0025-5610
1436-4646
DOI:10.1007/s10107-008-0246-5