A new bound for the quadratic assignment problem based on convex quadratic programming
- Cite this article as:
- Anstreicher, K. & Brixius, N. Math. Program. (2001) 89: 341. doi:10.1007/PL00011402
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We describe a new convex quadratic programming bound for the quadratic assignment problem (QAP). The construction of the bound uses a semidefinite programming representation of a basic eigenvalue bound for QAP. The new bound dominates the well-known projected eigenvalue bound, and appears to be competitive with existing bounds in the trade-off between bound quality and computational effort.