A new bound for the quadratic assignment problem based on convex quadratic programming

Kurt M Anstreicher; Nathan W Brixius

doi:10.1007/PL00011402

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A new bound for the quadratic assignment problem based on convex quadratic programming

Journal article

Peer reviewed

A new bound for the quadratic assignment problem based on convex quadratic programming

Kurt M Anstreicher and Nathan W Brixius

Mathematical programming, Vol.89(3), pp.341-357

02/01/2001

DOI: 10.1007/PL00011402

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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.

Applied Sciences

Exact sciences and technology

Mathematical programming

Operational research and scientific management

Operational research. Management science

Details

Title: Subtitle: A new bound for the quadratic assignment problem based on convex quadratic programming
Creators: Kurt M Anstreicher - University of Iowa
Nathan W Brixius - University of Iowa
Resource Type: Journal article
Publication Details: Mathematical programming, Vol.89(3), pp.341-357
Publisher: Springer
DOI: 10.1007/PL00011402
ISSN: 0025-5610
eISSN: 1436-4646
Language: English
Date published: 02/01/2001
Academic Unit: Business Analytics; Industrial and Systems Engineering; Computer Science
Record Identifier: 9984380430402771

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