Description

If the feasible set is defined in terms of variables that don't appear
in the VI function F, we should not need to mention these variables
explicitly in a match.  Any unmatched variable will be treated as
matched to the zero function.  The optimization analogy is variables
that appear in the constraints but not in the objective.  We
test/define the proper behavior in this model.

Contributor: Steven Dirkse, February 2009

Small Model of Type : VI

Category : GAMS EMP library

Main file : zerofunc.gms

$title Match unmatched vars with zero functions in VI (ZEROFUNC,SEQ=18)

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If the feasible set is defined in terms of variables that don't appear
in the VI function F, we should not need to mention these variables
explicitly in a match.  Any unmatched variable will be treated as
matched to the zero function.  The optimization analogy is variables
that appear in the constraints but not in the objective.  We
test/define the proper behavior in this model.

Contributor: Steven Dirkse, February 2009

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First we define an NLP in two variables, then write down the MCP version,
then write down the VI version.

     General case                       Specific case
NLP: min f(x)                           1/3 y^3
    s.t. g(x) >= 0                      y >= sqr(z)
        L <= x <= U                     y, z free

MCP: take derivatives of Lagrangian function wrt x,u
     dfdx - u * dgdx  perpto x          y^2 - u*1  perpto y free
                                        0   + u*2z perpto z free
     g(x)             perpto u >= 0     y - sqr(z) perpto u >= 0

VI:  F(x) := dfdx,                      F_y := y^2
                                        F_z := 0
 X = {x:g(x) >= 0, L <= x <= U }        y >= sqr(z), y, z in bounds

All of this to show/test that it is not necessary to include the pair
F_z.z in the model statement, and that since z is not mentioned
explicitly in a match, it is matched with the zero function.
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free variables y, z;
free variable obj;
equation objDef, gCons;

objDef..  obj =E= power(y,3) / 3;
gCons..   y   =G= sqr(z);

model mNLP / objDef, gCons /;
solve mNLP min obj using nlp;


positive variable u 'explicit multiplier for MCP';
u.l = gCons.m;
equations
  dLdy, dLdz,
  dLdu;

dLdy..  sqr(y)     - u     =N= 0;
dLdz..  0          - u*2*z =N= 0;
dLdu..  y - sqr(z)         =N= 0;

model mMCP / dLdy.y, dLdz.z, dLdu.u /;
solve mMCP using mcp;
abort$[mMCP.iterusd > 0] 'should have started at MCP solution!';

equations
  F_y 'dfdy'
  F_z 'dfdz'
  ;
F_y.. sqr(y) =N= 0;
F_z.. 0 =N= 0;

model mVI / F_y, gCons /;
model mVI0 / F_z, F_y, gCons /;

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N.B.: we test 4 equivalent ways to specify the same VI.  The VI statement
always contains the matching pair "F_y y" and "gCons", the equation defining
the constraint set. Each variant specifies the matching between the "z"
variable and the zero mapping differently. 
  1) z appears right after the "vi" keyword: it is in the VI and perpendicular
     to 0 (null) functions.
  2) z is matched with F_z := 0.
  3) z is matched with "0", representing zero functions.
  4) a variant of (3), where the order of the pair "0 z" and "F_y y" has been
     swapped.

Cases 3 and 4 use EMP info file syntax introduced with GAMS 25.1.

For this trivial case of a single VI these differences are not
important, but when combining VI models and max/min models as
different agents in an equilibrium model the differences do matter.
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file myinfo / '%emp.info%' /;

* case 1)
putclose myinfo  'vi  z   F_y y  gCons' /;
solve mVI using emp;
abort$[mVI.modelStat <> %modelStat.locallyOptimal%] 'VI should solve OK';
abort$[mVI.solveStat <> %solveStat.normalCompletion%] 'VI should solve OK';
abort$[mVI.iterusd > 0] 'should have started at VI solution!';

* case 2)
putclose myinfo  'vi  F_z z  F_y y  gCons' /;
solve mVI0 using emp;
abort$[mVI0.modelStat <> %modelStat.locallyOptimal%] 'VI should solve OK';
abort$[mVI0.solveStat <> %solveStat.normalCompletion%] 'VI should solve OK';
abort$[mVI0.iterusd > 0] 'should have started at VI solution!';

* case 3)
putclose myinfo  'vi  0 z  F_y y  gCons' /;
solve mVI using emp;
abort$[mVI.modelStat <> %modelStat.locallyOptimal%] 'VI should solve OK';
abort$[mVI.solveStat <> %solveStat.normalCompletion%] 'VI should solve OK';
abort$[mVI.iterusd > 0] 'should have started at VI solution!';

* case 4)
putclose myinfo  'vi  F_y y  0 z  gCons' /;
solve mVI using emp;
abort$[mVI.modelStat <> %modelStat.locallyOptimal%] 'VI should solve OK';
abort$[mVI.solveStat <> %solveStat.normalCompletion%] 'VI should solve OK';
abort$[mVI.iterusd > 0] 'should have started at VI solution!';