A new bound for the quadratic assignment problem based on convex quadratic programming |
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| Authors: | Kurt M. Anstreicher Nathan W. Brixius |
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| Affiliation: | (1) Department of Management Sciences, University of Iowa, Iowa City, IA 52242, e-mail: kurt-anstreicher@uiowa.edu, US;(2) Department of Computer Science, University of Iowa, Iowa City, IA 52242, e-mail: brixius@cs.uiowa.edu, US |
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| Abstract: | 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. Received: February 2000 / Accepted: November 2000?Published online January 17, 2001 |
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| Keywords: | : quadratic assignment problem – eigenvalue bounds – quadratic programming – semidefinite programming |
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