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Instance: abel

Formats ams gms lp mod nl osil pip
Primal Bounds
225.19458320 p1 ( gdx sol )
(infeas: 5e-14)
Dual Bounds
225.19458320 (ANTIGONE)
225.19458300 (BARON)
225.19458320 (LINDO)
225.19458320 (SCIP)
References Kendrick, D, Caution and Probing in a Macroeconomic Model, Journal of Economic Dynamics and Control, 4:1, 1982, 149-170.
Source GAMS Model Library model abel
Application Linear Quadratic Control
Added to library 31 Jul 2001
Problem type QP
#Variables 30
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 30
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type quadratic
Objective curvature convex
#Nonzeros in Objective 30
#Nonlinear Nonzeros in Objective 30
#Constraints 14
#Linear Constraints 14
#Quadratic Constraints 0
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature linear
#Nonzeros in Jacobian 70
#Nonlinear Nonzeros in Jacobian 0
#Nonzeros in (Upper-Left) Hessian of Lagrangian 30
#Nonzeros in Diagonal of Hessian of Lagrangian 30
#Blocks in Hessian of Lagrangian 30
Minimal blocksize in Hessian of Lagrangian 1
Maximal blocksize in Hessian of Lagrangian 1
Average blocksize in Hessian of Lagrangian 1.0
#Semicontinuities 0
#Nonlinear Semicontinuities 0
#SOS type 1 0
#SOS type 2 0
Infeasibility of initial point 7.252
Sparsity Jacobian Sparsity of Objective Gradient and Jacobian
Sparsity Hessian of Lagrangian Sparsity of Hessian of Lagrangian

$offlisting
*  
*  Equation counts
*      Total        E        G        L        N        X        C        B
*         15       15        0        0        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*         31       31        0        0        0        0        0        0
*  FX      2
*  
*  Nonzero counts
*      Total    const       NL      DLL
*        101       71       30        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,x17,x18,x19
          ,x20,x21,x22,x23,x24,x25,x26,x27,x28,x29,x30,objvar;

Equations  e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12,e13,e14,e15;


e1.. -(0.5*((-24.24375 + 0.0625*x1)*(-387.9 + x1) + (-85.3 + x9)*(-85.3 + x9)
      + (-24.425578125 + 0.0625*x2)*(-390.80925 + x2) + (-85.93975 + x10)*(-
     85.93975 + x10) + (-24.6087699609375 + 0.0625*x3)*(-393.740319375 + x3) + 
     (-86.584298125 + x11)*(-86.584298125 + x11) + (-24.7933357356445 + 0.0625*
     x4)*(-396.693371770313 + x4) + (-87.2336803609375 + x12)*(-
     87.2336803609375 + x12) + (-24.9792857536619 + 0.0625*x5)*(-
     399.66857205859 + x5) + (-87.8879329636445 + x13)*(-87.8879329636445 + x13
     ) + (-25.1666303968143 + 0.0625*x6)*(-402.666086349029 + x6) + (-
     88.5470924608719 + x14)*(-88.5470924608719 + x14) + (-25.3553801247904 + 
     0.0625*x7)*(-405.686081996647 + x7) + (-89.2111956543284 + x15)*(-
     89.2111956543284 + x15) + (-2554.55454757264 + 6.25*x8)*(-408.728727611622
      + x8) + (-8988.02796217359 + 100*x16)*(-89.8802796217359 + x16)) + 0.5*((
     -110.5 + x17)*(-110.5 + x17) + (-65.3124 + 0.444*x24)*(-147.1 + x24) + (-
     111.32875 + x18)*(-111.32875 + x18) + (-65.802243 + 0.444*x25)*(-148.20325
      + x25) + (-112.163715625 + x19)*(-112.163715625 + x19) + (-66.2957598225
      + 0.444*x26)*(-149.314774375 + x26) + (-113.004943492188 + x20)*(-
     113.004943492188 + x20) + (-66.7929780211688 + 0.444*x27)*(-
     150.434635182813 + x27) + (-113.852480568379 + x21)*(-113.852480568379 + 
     x21) + (-67.2939253563275 + 0.444*x28)*(-151.562894946684 + x28) + (-
     114.706374172642 + x22)*(-114.706374172642 + x22) + (-67.7986297965 + 
     0.444*x29)*(-152.699616658784 + x29) + (-115.566671978937 + x23)*(-
     115.566671978937 + x23) + (-68.3071195199738 + 0.444*x30)*(-
     153.844863783725 + x30))) + objvar =E= 0;

e2..  - 0.914*x1 + x2 + 0.016*x9 - 0.305*x17 - 0.424*x24 =E= -59.4;

e3..  - 0.914*x2 + x3 + 0.016*x10 - 0.305*x18 - 0.424*x25 =E= -59.4;

e4..  - 0.914*x3 + x4 + 0.016*x11 - 0.305*x19 - 0.424*x26 =E= -59.4;

e5..  - 0.914*x4 + x5 + 0.016*x12 - 0.305*x20 - 0.424*x27 =E= -59.4;

e6..  - 0.914*x5 + x6 + 0.016*x13 - 0.305*x21 - 0.424*x28 =E= -59.4;

e7..  - 0.914*x6 + x7 + 0.016*x14 - 0.305*x22 - 0.424*x29 =E= -59.4;

e8..  - 0.914*x7 + x8 + 0.016*x15 - 0.305*x23 - 0.424*x30 =E= -59.4;

e9..  - 0.097*x1 - 0.424*x9 + x10 + 0.101*x17 - 1.459*x24 =E= -184.7;

e10..  - 0.097*x2 - 0.424*x10 + x11 + 0.101*x18 - 1.459*x25 =E= -184.7;

e11..  - 0.097*x3 - 0.424*x11 + x12 + 0.101*x19 - 1.459*x26 =E= -184.7;

e12..  - 0.097*x4 - 0.424*x12 + x13 + 0.101*x20 - 1.459*x27 =E= -184.7;

e13..  - 0.097*x5 - 0.424*x13 + x14 + 0.101*x21 - 1.459*x28 =E= -184.7;

e14..  - 0.097*x6 - 0.424*x14 + x15 + 0.101*x22 - 1.459*x29 =E= -184.7;

e15..  - 0.097*x7 - 0.424*x15 + x16 + 0.101*x23 - 1.459*x30 =E= -184.7;

* set non-default bounds
x1.fx = 387.9;
x9.fx = 85.3;

* set non-default levels
x2.l = 387.9;
x3.l = 387.9;
x4.l = 387.9;
x5.l = 387.9;
x6.l = 387.9;
x7.l = 387.9;
x8.l = 387.9;
x10.l = 85.3;
x11.l = 85.3;
x12.l = 85.3;
x13.l = 85.3;
x14.l = 85.3;
x15.l = 85.3;
x16.l = 85.3;
x17.l = 110.5;
x18.l = 110.5;
x19.l = 110.5;
x20.l = 110.5;
x21.l = 110.5;
x22.l = 110.5;
x23.l = 110.5;
x24.l = 147.1;
x25.l = 147.1;
x26.l = 147.1;
x27.l = 147.1;
x28.l = 147.1;
x29.l = 147.1;
x30.l = 147.1;

Model m / all /;

m.limrow=0; m.limcol=0;
m.tolproj=0.0;

$if NOT '%gams.u1%' == '' $include '%gams.u1%'

$if not set NLP $set NLP NLP
Solve m using %NLP% minimizing objvar;


Last updated: 2018-05-28 Git hash: ac4a64c1
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