Version:

pmedian.gms : P-Median problem

**Description**

The pmedian problem is defined as follows: given a set I={1...n} of locations and a transportation cost W between each pair of locations. Select a subset S of p location minimizing the sum of the distances between each location and the closest one in S. There are currently 40 data files from the OR-LIB http://people.brunel.ac.uk/~mastjjb/jeb/orlib/pmedinfo.html These data files are the 40 test problems from Table 2 of J.E.Beasley "A note on solving large p-median problems" European Journal of Operational Research 21 (1985) 270-273. pmed15 1729 1734

**Large Model of Type :** MINLP

**Category :** GAMS Model library

**Main file :** pmedian.gms **includes :** pmed15.inc

```
$title P-Median Problem (PMEDIAN,SEQ=408)
$onText
The pmedian problem is defined as follows: given a set I={1...n} of
locations and a transportation cost W between each pair of
locations. Select a subset S of p location minimizing the sum of the
distances between each location and the closest one in S.
There are currently 40 data files from the OR-LIB
http://people.brunel.ac.uk/~mastjjb/jeb/orlib/pmedinfo.html
These data files are the 40 test problems from Table 2 of
J.E.Beasley "A note on solving large p-median problems" European
Journal of Operational Research 21 (1985) 270-273.
pmed15 1729 1734
J.E.Beasley "A note on solving large p-median problems" European
Journal of Operational Research 21 (1985) 270-273.
Keywords: mixed integer linear programming, mixed integer nonlinear programming,
p-median problem, facility location problem
$offText
$if not set instance $set instance pmed15.inc
$if not exist "%instance%" $abort File of instance does not exist
$onEchoV > pm.awk
BEGIN { nr=0 }
!/^#/ {
if (nr==0) {
n = $1;
printf("set n /0*%d/; Scalar p /%d/;\n", n-1,$3);
printf("Table w(n,n) distances\n$onDelim\nn");
for (i=0; i<n; i++) printf(",%d",i);
} if (nr>0)
printf("\n%d %s",nr-1,$0);
nr++;
}
END {
printf("\n$offDelim\n;")
}
$offEcho
$set fn %gams.scrdir%tlinst.%gams.scrext%
$call awk -f pm.awk %instance% > "%fn%"
$ifE errorLevel<>0 $abort problems with awk call
$offListing
$include "%fn%"
$onListing
Alias (n,i,j);
Scalar wMax;
wMax = smax((i,j), w(i,j));
Variable
x(n) 'location selection'
costs(n,n) 'costs between location i and j'
cost(n) 'cost to serve i'
obj 'objective';
Binary Variable x;
Equation
defp 'select p locations'
defcosts(i,j) 'costs between location i and j is w(i,j) or inf (=2*wMax))'
defcost(i) 'cost to serve i is the smallest cost between i and other locations'
defobj 'objective';
$ifThen set MIP
Positive Variable diff(i,j);
Binary Variable bdiff(i,j);
Equation defcosts2(i,j), defdiffZero(i,j);
defcosts(i,j).. costs(i,j) =g= 2*wMax - 2*wMax*x(j);
defcosts2(i,j).. cost(i) =e= costs(i,j) - diff(i,j);
defdiffZero(i,j).. diff(i,j) =l= 2*wMax - 2*wMax*bdiff(i,j);
defcost(i).. sum(j, bdiff(i,j)) =g= 1;
$else
defcosts(i,j).. costs(i,j) =e= ifthen (x(j) >= 0.5, w(i,j), 2*wMax);
defcost(i).. cost(i) =e= smin(j, costs(i,j));
$endIf
defp.. sum(n, x(n)) =e= p;
defobj.. obj =e= sum(n, cost(n));
Model pmedian / all /;
costs.lo(i,j) = w(i,j);
$ifThen set MIP
solve pmedian using mip min obj;
$else
solve pmedian using minlp min obj;
$endIf
```