Algorithm 769: Fortran subroutines for approximate solution of sparse quadratic assignment problems using GRASP

Authors:
Panos M. Pardalos;Leonidas S. Pitsoulis;Mauricio G. C. Resende
Affiliations:
Univ. of Florida, Gainsville;Univ. of Florida, Gainsville;AT&T Labs, Florham Park, NJ
Venue:
ACM Transactions on Mathematical Software (TOMS)
Year:
1997

Citing 2
Cited 4

Algorithm 754: Fortran subroutines for approximate solution of dense quadratic assignment problems using GRASP

ACM Transactions on Mathematical Software (TOMS)
A More Portable Fortran Random Number Generator

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Probability Distribution of Solution Time in GRASP: An Experimental Investigation

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Generating Hard Test Instances with Known Optimal Solution for the Rectilinear Quadratic Assignment Problem

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Extensive Testing of a Hybrid Genetic Algorithm for Solving Quadratic Assignment Problems

Computational Optimization and Applications
Remark on Algorithm 769: Fortran subroutines for approximate solution of sparse quadratic assignment problems using GRASP

ACM Transactions on Mathematical Software (TOMS)

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Abstract

We describe Fortran subroutines for finding approximate solutions of sparse instances of the Quadratic Assignment Problem (QAP) using a Greedy Randomized Adaptive Search Procedure (GRASP). The design and implementation of the code are described in detail. Computational results comparing the new subroutines with a dense version of the code (Algorithm 754, ACM TOMS) show that the speedup increases with the sparsity of the data.