Operations, Information and Decisions Papers

Document Type

Journal Article

Date of this Version

7-2008

Publication Source

Computational Optimization and Applications

Volume

40

Start Page

351

Last Page

372

DOI

10.1007/s10589-007-9093-1

Abstract

This paper reports on a new algorithm for the Generalized Quadratic Assignment problem (GQAP). The GQAP describes a broad class of quadratic integer programming problems, wherein M pair-wise related entities are assigned to N destinations constrained by the destinations’ ability to accommodate them. This new algorithm is based on a Reformulation Linearization Technique (RLT) dual ascent procedure. Experimental results show that the runtime of this algorithm is as good or better than other known exact solution methods for problems as large as M=20 and N=15.

Keywords

combinatorial optimization, branch-and-bound, quadratic assignment problem, reformulation linearization technique, lagrangian dual, dual ascent procedure

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Date Posted: 27 November 2017

This document has been peer reviewed.