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: [R.E. Burkard, S.E. Karisch, F. Rendl. QAPLIB — a quadratic assignment problem library. Journal on Global Optimization, 10: 291–403, 1997]. AMS classification: 90C22, 20Cxx, 70-08.
|Place of Publication||Tilburg|
|Number of pages||21|
|Publication status||Published - 2007|
|Name||CentER Discussion Paper|
- quadratic assignment problem
- semidefinite programming
- group sym- metry