Exploiting group symmetry in semidefinite programming relaxations of the quadratic assignment problem
نویسندگان
چکیده
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].
منابع مشابه
Improved semidefinite programming bounds for quadratic assignment problems with suitable symmetry
Semidefinite programming (SDP) bounds for the quadratic assignment problem (QAP) were introduced in: [Q. Zhao, S.E. Karisch, F. Rendl, and H. Wolkowicz. Semidefinite Programming Relaxations for the Quadratic Assignment Problem. Journal of Combinatorial Optimization, 2, 71–109, 1998.] Empirically, these bounds are often quite good in practice, but computationally demanding, even for relatively s...
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ورودعنوان ژورنال:
- Math. Program.
دوره 122 شماره
صفحات -
تاریخ انتشار 2010