Affiliation:
1. AT&T Bell Labs, Murray Hill, NJ
2. Univ. of Florida, Gainesville
3. Pennsylvania State Univ., University Park
Abstract
In the NP-complete quadratic assignment problem (QAP),
n
facilities are to be assigned to
n
sites at minimum cost. The contribution of assigning facility
i
to site
k
and facility
j
to site
l
to the total cost is
f
ij
d
kl
, where
f
ij
is the flow between facilities
i
and
j
, and
d
kl
is the distance between sites
k
and
l
. Only very small (
n
≤20) instances of the QAP have been solved exactly, and heuristics are therefore used to produce approximate solutions. This article describes a set of Fortran subroutines to find approximate solutions to dense quadratic assignment problems, having at least one symmetric flow or distance matrix. A greedy, randomized, adaptive search procedure (GRASP) is used to produce the solutions. The design and implementation of the code are described in detail, and extensive computational experiments are reported, illustrating solution quality as a function of running time.
Publisher
Association for Computing Machinery (ACM)
Subject
Applied Mathematics,Software
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