stablem.gms : Stable Marriage Problem

Description

```Given a set of n men and n women, marry them off in pairs after each
man has ranked the women in order of preference from 1 to n,
{w_1,...,w_n} and each women has done likewise, {m_1,...,m_n}. If the
resulting set of marriages contains no pairs of the form {m_i,w_j},
{m_k,w_l} such that m_i prefers w_l to w_j and w_l prefers m_i to m_k,
the marriage is said to be stable. Gale and Shapley (1962) showed that
a stable marriage exists for any choice of rankings (Skiena 1990,
p. 245). In the United States, the algorithm of Gale and Shapley
(1962) is used to match hospitals to medical interns (Skiena 1990,
p. 245).

This model generates multiple/all solution by introducing MIP cuts
and resolving the MIP.
```

Small Model of Type : MIP

Category : GAMS Model library

Main file : stablem.gms

``````\$title Stable Marriage Problem (STABLEM,SEQ=389)

\$onText
Given a set of n men and n women, marry them off in pairs after each
man has ranked the women in order of preference from 1 to n,
{w_1,...,w_n} and each women has done likewise, {m_1,...,m_n}. If the
resulting set of marriages contains no pairs of the form {m_i,w_j},
{m_k,w_l} such that m_i prefers w_l to w_j and w_l prefers m_i to m_k,
the marriage is said to be stable. Gale and Shapley (1962) showed that
a stable marriage exists for any choice of rankings (Skiena 1990,
p. 245). In the United States, the algorithm of Gale and Shapley
(1962) is used to match hospitals to medical interns (Skiena 1990,
p. 245).

This model generates multiple/all solution by introducing MIP cuts
and resolving the MIP.

Gale, D, and Shapley, L S, College admissions and the stability of
marriage. American Mathematical Monthly 69, 1 (1962), 9-15.

Gusfield, D, and Irving, R W, The stable marriage problem: structure
and algorithms. MIT Press, Cambridge, MA, USA, 1989.

Skiena, S, 6.4.4. Stable Marriages. In Implementing discrete mathematics:
combinatorics and graph theory with Mathematica. Addison-Wesley Longman
Publishing Co., Inc., Boston, MA, USA, 1991.

Weisstein, E W, Stable Marriage Problem. From MathWorld-A Wolfram Web
Resource. http://mathworld.wolfram.com/StableMarriageProblem.html

Sethuraman, V J, and Teo, C P, Linear programming brings marital
bliss. Mathematical Medley, Singapore Mathematical Society 25, 2
(1998).

Keywords: mixed integer linear programming, marriage problem, matching
\$offText

* use gams ... --data=xxx
\$if not set data   \$set data premer
\$if not set maxsol \$set maxsol 100

\$ifThenI %data% == premer
Set
m / Alan, Bob, Carl, Dan         /
w / Alice, Brenda, Cindy, Debbie /;

Table wp(w,m) 'woman preferences'
Alan Bob Carl Dan
Alice      3   4    2   1
Brenda     3   4    1   2
Cindy      3   2    1   4
Debbie     4   2    3   1;

Table mp(m,w) 'man preferences'
Alice Brenda Cindy Debbie
Alan       2      4     1      3
Bob        1      4     2      3
Carl       3      4     2      1
Dan        3      2     1      4;

\$elseIfI %data% == minizinc
Set
m / m1*m5 /
w / w1*w5 /;

Table wp(w,m) 'woman preferences'
m1 m2 m3 m4 m5
w1   1  2  4  3  5
w2   3  5  1  2  4
w3   5  4  2  1  3
w4   1  3  5  4  2
w5   4  2  3  5  1;

Table mp(m,w) 'man preferences'
w1 w2 w3 w4 w5
m1   5  1  2  4  3
m2   4  1  3  2  5
m3   5  3  2  4  1
m4   1  5  4  3  2
m5   4  3  2  1  5;

\$elseIfI %data% == five
Set
m / Joe, Brian, George, Matt, Jim    /
w / Amy, Sarah, Susan, Kelly, Dianne /;

Table wp(w,m) 'woman preferences'
Joe Brian George Matt Jim
Amy       1     2      4    3   5
Sarah     3     5      1    2   4
Susan     5     4      2    1   3
Kelly     1     3      5    4   2
Dianne    4     2      3    5   1;

Table mp(m,w) 'man preferences'
Amy Sarah Susan Kelly Dianne
Joe       5     1     2     4      3
Brian     4     1     3     2      5
George    5     3     2     4      1
Matt      1     5     4     3      2
Jim       4     3     2     1      5;

\$elseIfI %data% == mathworld
Set
m / m1*m9 /
w / w1*w9 /;

Table wp(w,m) 'woman preferences'
m1 m2 m3 m4 m5 m6 m7 m8 m9
w1   3  9  3  8  6  2  9  6  8
w2   1  4  1  7  9  4  3  3  2
w3   5  8  8  5  2  5  8  2  6
w4   2  1  9  3  5  1  2  1  4
w5   8  7  5  2  1  6  7  8  9
w6   7  6  4  6  4  8  5  4  1
w7   6  3  2  4  7  3  4  5  3
w8   9  2  6  9  3  9  6  9  7
w9   4  5  7  1  8  7  1  7  5;

Table mp(m,w) 'man preferences'
w1 w2 w3 w4 w5 w6 w7 w8 w9
m1   7  5  4  9  2  2  1  5  6
m2   3  4  8  7  6  7  6  6  1
m3   8  8  3  4  4  8  2  9  4
m4   9  3  9  2  9  6  3  1  7
m5   6  1  7  5  8  5  8  2  5
m6   4  2  5  8  7  3  5  8  8
m7   2  6  6  3  5  4  4  4  3
m8   1  7  1  1  1  1  9  3  9
m9   5  9  2  6  3  9  7  7  2;

\$else
\$abort dataset "%data%" does not exist, use: premer,five,minizinc
\$endIf

Alias (m,mm), (w,ww);

Binary Variable match(w,m);

Variable rank;

Equation onem(w), onew(m), stable(w,m), defrank;

defrank.. rank =e= sum((w,m), wp(w,m)*match(w,m));

onem(w).. sum(m, match(w,m)) =e= 1;

onew(m).. sum(w, match(w,m)) =e= 1;

stable(w,m).. sum(mm\$(wp(w,mm) > wp(w,m)), match(w,mm))
+ sum(ww\$(mp(m,ww) > mp(m,w)), match(ww,m)) =l= 1;

Model sm / all /;

solve sm using mip minimizing rank;

Set
nn 'number of solutions' / sol-1*sol-%maxsol% /
n(nn)
sol(nn,w,m);

Equation cut(nn);

cut(n).. sum(sol(n,w,m), match(w,m)) =l= card(w) - 1;

Model new / sm, cut /;

new.modelStat = sm.modelStat;
option limRow = 0, limCol = 0, solPrint = off, optCr = 0, solveLink = 5;

loop(nn\$(new.modelStat = 1),
n(nn) = yes;
sol(nn,w,m) = round(match.l(w,m));
solve new using mip minimizing rank;
);
option  sol:0:0:1;
display sol;
``````
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