Description

Test problem 9.3.8 in Handbook of Test Problems in Local and Global Optimization
Test problem 9.2.7 on http://titan.princeton.edu/TestProblems/chapter9.html

References:

Floudas, C A, Pardalos, P M, Adjiman, C S, Esposito, W R, Gumus, Z H, Harding,
S T, Klepeis, J L, Meyer, C A, and Schweiger, C A, Handbook of Test Problems in
Local and Global Optimization. Kluwer Academic Publishers, 1999

Visweswaran, V., C. Floudas, M. Ierapetritou, and E. Pistikopoulos, A
Decomposition Based Global Optimization Approach for Solving Bilevel Linear and
Nonlinear Quadratic Programs. In Floudas and Pardalos (eds.), State of the Art
in Global Optimization: Computational Methods and Applications. Kluwer Academic
Publishers, 1996.

Contributor: Jan-H. Jagla, January 2010

Small Model of Type : BP

Category : GAMS EMP library

Main file : flds927.gms

$title Princeton Bilevel Optimization Example 9.2.7 (FLDS927,SEQ=42)

$ontext

  Test problem 9.3.8 in Handbook of Test Problems in Local and Global Optimization
  Test problem 9.2.7 on http://titan.princeton.edu/TestProblems/chapter9.html

References:

Floudas, C A, Pardalos, P M, Adjiman, C S, Esposito, W R, Gumus, Z H, Harding,
S T, Klepeis, J L, Meyer, C A, and Schweiger, C A, Handbook of Test Problems in
Local and Global Optimization. Kluwer Academic Publishers, 1999

Visweswaran, V., C. Floudas, M. Ierapetritou, and E. Pistikopoulos, A
Decomposition Based Global Optimization Approach for Solving Bilevel Linear and
Nonlinear Quadratic Programs. In Floudas and Pardalos (eds.), State of the Art
in Global Optimization: Computational Methods and Applications. Kluwer Academic
Publishers, 1996.

Contributor: Jan-H. Jagla, January 2010

$offtext

*Solution of problem 9.2.7 on the web
scalar  x_l /    1 /
        y_l /    0 /
        tol / 1e-6 /;

variables z, z_in, y; positive variable x;
equations ob, c0, c1, c2, c3, c4;

ob.. sqr(x - 5) + sqr(2*y + 1)           =e=    z;

c0..                  sqr(y-1) - 1.5*x*y =e= z_in;
c1..       -3*x +            y           =l=   -3;
c2..          x -        0.5*y           =l=    4;
c3..          x +            y           =l=    7;
c4..            -            y           =l=    0;

model bilevel / all /;

$echo bilevel x min z_in y c0 c1 c2 c3 c4 > "%emp.info%"

*Start from reported solution
x.l = x_l;
y.l = y_l;

solve bilevel using EMP minimizing z;

abort$(   (abs(x.l - x_l) > tol)
       or (abs(y.l - y_l) > tol) ) 'Deviated from reported solution';