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Instance pricing050

A firm seeks to determine the price of several new products to enter a competitive market.
Formats ams gms mod nl osil py
Primal Bounds (infeas ≤ 1e-08)
-1813.82907800 p1 ( gdx sol )
(infeas: 7e-10)
Other points (infeas > 1e-08)  
Dual Bounds  
References Davarnia, Danial, Strong relaxations for continuous nonlinear programs based on decision diagrams, Operations Research Letters, 49:2, 2021, 239-245.
Davarnia, Danial and van Hoeve, Willem-Jan, Outer approximation for integer nonlinear programs via decision diagrams, Mathematical Programming, 187:1, 2021, 111-150.
Source Mohammadreza Kiaghadi
Application Marketing
Added to library 25 Mar 2024
Problem type NLP
#Variables 50
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 50
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense max
Objective type linear
Objective curvature linear
#Nonzeros in Objective 46
#Nonlinear Nonzeros in Objective 0
#Constraints 5
#Linear Constraints 0
#Quadratic Constraints 0
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 5
Operands in Gen. Nonlin. Functions exp mul power sqr
Constraints curvature nonconcave
#Nonzeros in Jacobian 249
#Nonlinear Nonzeros in Jacobian 249
#Nonzeros in (Upper-Left) Hessian of Lagrangian 50
#Nonzeros in Diagonal of Hessian of Lagrangian 50
#Blocks in Hessian of Lagrangian 50
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
Minimal coefficient 1.0000e-03
Maximal coefficient 2.0000e+01
Infeasibility of initial point 984
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
*         6        1        0        5        0        0        0        0
*
* Variable counts
*                  x        b        i      s1s      s2s       sc       si
*     Total     cont   binary  integer     sos1     sos2    scont     sint
*        51       51        0        0        0        0        0        0
* FX      0
*
* Nonzero counts
*     Total    const       NL
*       296        1      295

* Solve m using NLP maximizing objvar;

Variables
    objvar,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,x31,x32,x33,x34,x35,x36,x37,x38,x39,
    x40,x41,x42,x43,x44,x45,x46,x47,x48,x49,x50,x51;

Equations
    e1,e2,e3,e4,e5,e6;

e1..  -x2 - 20 * x3 - 7 * x4 - 13 * x6 - 2 * x7 - 15 * x8 - 10 * x9 - 15 * x11
      - 20 * x12 - 13 * x13 - 18 * x14 - 11 * x15 - 10 * x16 - 6 * x17 - 16 *
      x18 - 20 * x19 - 12 * x20 - 6 * x21 - 16 * x22 - 4 * x23 - 15 * x24 - 17
      * x25 - 17 * x26 - 13 * x28 - 7 * x29 - 6 * x30 - 16 * x31 - 16 * x32 -
      14 * x33 - 13 * x34 - 15 * x35 - 10 * x36 - 20 * x37 - 10 * x38 - 5 * x39
      - 18 * x40 - 15 * x41 - x42 - 10 * x44 - 7 * x45 - 12 * x46 - 5 * x47 -
      11 * x48 - 18 * x49 - 13 * x50 - 15 * x51 - objvar =E= 0;
e2..  -2.9 * x2 * exp(-0.0010000000000000002 * power(x2, 3)) - 2.1 * x3 * exp(-
      0.0010000000000000002 * power(x3, 3)) - 1.7 * x4 * exp(-
      0.010000000000000002 * sqr(x4)) - 9.2 * x5 * exp(-0.0010000000000000002
      * power(x5, 3)) - 5.7 * x6 * exp(-0.010000000000000002 * sqr(x6)) - 0.9
      * x7 * exp(-0.0010000000000000002 * power(x7, 3)) - 7.5 * x8 * exp(-
      0.010000000000000002 * sqr(x8)) - 3.6 * x9 * exp(-0.1 * x9) - 2.1 * x10
      * exp(-0.1 * x10) - 4.9 * x11 * exp(-0.0010000000000000002 * power(x11,
      3)) - 0.9 * x12 * exp(-0.010000000000000002 * sqr(x12)) - 5.6 * x13 * exp
      (-0.1 * x13) - 9.3 * x14 * exp(-0.0010000000000000002 * power(x14, 3)) -
      3.5 * x15 * exp(-0.010000000000000002 * sqr(x15)) - 3.1 * x16 * exp(-0.1
      * x16) - 6.1 * x17 * exp(-0.1 * x17) - 3.9 * x18 * exp(-0.1 * x18) - 6.6
      * x19 * exp(-0.010000000000000002 * sqr(x19)) - 8.4 * x20 * exp(-
      0.0010000000000000002 * power(x20, 3)) - 2.5 * x21 * exp(-
      0.0010000000000000002 * power(x21, 3)) - 5.4 * x22 * exp(-0.1 * x22) -
      5.2 * x23 * exp(-0.0010000000000000002 * power(x23, 3)) - 1.9 * x24 * exp
      (-0.0010000000000000002 * power(x24, 3)) - 5.5 * x25 * exp(-
      0.010000000000000002 * sqr(x25)) - 5.5 * x26 * exp(-0.1 * x26) - 4.9 *
      x27 * exp(-0.0010000000000000002 * power(x27, 3)) - 0.5 * x28 * exp(-0.1
      * x28) - 6.7 * x29 * exp(-0.1 * x29) - 4.5 * x30 * exp(-0.1 * x30) - 0.4
      * x31 * exp(-0.010000000000000002 * sqr(x31)) - 7.1 * x32 * exp(-0.1 *
      x32) - 1.5 * x33 * exp(-0.010000000000000002 * sqr(x33)) - 2.4 * x34 *
      exp(-0.010000000000000002 * sqr(x34)) - 3.3 * x35 * exp(-
      0.010000000000000002 * sqr(x35)) - 3.2 * x36 * exp(-0.0010000000000000002
      * power(x36, 3)) - 9.2 * x37 * exp(-0.010000000000000002 * sqr(x37)) - 3
      * x38 * exp(-0.0010000000000000002 * power(x38, 3)) - 6.9 * x39 * exp(
      -0.1 * x39) - 0.4 * x40 * exp(-0.1 * x40) - 2.3 * x41 * exp(-
      0.0010000000000000002 * power(x41, 3)) - 3.1 * x42 * exp(-
      0.0010000000000000002 * power(x42, 3)) - 3.6 * x43 * exp(-
      0.0010000000000000002 * power(x43, 3)) - 7.4 * x44 * exp(-
      0.010000000000000002 * sqr(x44)) - 8.9 * x45 * exp(-0.010000000000000002
      * sqr(x45)) - 5.8 * x46 * exp(-0.0010000000000000002 * power(x46, 3)) -
      0.3 * x47 * exp(-0.1 * x47) - 9 * x48 * exp(-0.0010000000000000002 *
      power(x48, 3)) - 1.4 * x49 * exp(-0.1 * x49) - 2.7 * x50 * exp(-
      0.0010000000000000002 * power(x50, 3)) - 4.8 * x51 * exp(-0.1 * x51) =L=
      -500;
e3..  -2.1 * x2 * exp(-0.0010000000000000002 * power(x2, 3)) - 8.3 * x3 * exp(-
      0.0010000000000000002 * power(x3, 3)) - 9 * x4 * exp(-0.1 * x4) - 5.6 *
      x5 * exp(-0.1 * x5) - 3 * x6 * exp(-0.010000000000000002 * sqr(x6)) - 6.4
      * x7 * exp(-0.1 * x7) - 7.7 * x8 * exp(-0.0010000000000000002 * power(x8
      , 3)) - 4.4 * x9 * exp(-0.1 * x9) - 1.3 * x10 * exp(-0.1 * x10) - 5.8 *
      x11 * exp(-0.010000000000000002 * sqr(x11)) - 8.6 * x12 * exp(-
      0.010000000000000002 * sqr(x12)) - 1.1 * x13 * exp(-0.010000000000000002
      * sqr(x13)) - 3.1 * x14 * exp(-0.0010000000000000002 * power(x14, 3)) -
      7.4 * x15 * exp(-0.010000000000000002 * sqr(x15)) - 4.2 * x16 * exp(-0.1
      * x16) - 5.6 * x17 * exp(-0.010000000000000002 * sqr(x17)) - 2.6 * x18 *
      exp(-0.1 * x18) - 6.5 * x19 * exp(-0.1 * x19) - 4.6 * x20 * exp(-
      0.0010000000000000002 * power(x20, 3)) - 4.3 * x21 * exp(-
      0.010000000000000002 * sqr(x21)) - 7.8 * x22 * exp(-0.010000000000000002
      * sqr(x22)) - 3.4 * x23 * exp(-0.010000000000000002 * sqr(x23)) - 1.6 *
      x24 * exp(-0.010000000000000002 * sqr(x24)) - 1.2 * x25 * exp(-
      0.0010000000000000002 * power(x25, 3)) - 8.7 * x26 * exp(-0.1 * x26) -
      0.8 * x27 * exp(-0.1 * x27) - 5 * x28 * exp(-0.010000000000000002 * sqr(
      x28)) - 3.7 * x29 * exp(-0.0010000000000000002 * power(x29, 3)) - 3.1 *
      x30 * exp(-0.010000000000000002 * sqr(x30)) - 0.7 * x31 * exp(-
      0.0010000000000000002 * power(x31, 3)) - 4.6 * x32 * exp(-
      0.0010000000000000002 * power(x32, 3)) - 3 * x33 * exp(-
      0.010000000000000002 * sqr(x33)) - 9.1 * x34 * exp(-0.0010000000000000002
      * power(x34, 3)) - 0.3 * x35 * exp(-0.010000000000000002 * sqr(x35)) -
      4.3 * x36 * exp(-0.1 * x36) - 2.1 * x37 * exp(-0.1 * x37) - 2.4 * x38 *
      exp(-0.010000000000000002 * sqr(x38)) - 6 * x39 * exp(-
      0.010000000000000002 * sqr(x39)) - 8.1 * x40 * exp(-0.010000000000000002
      * sqr(x40)) - 9.5 * x41 * exp(-0.1 * x41) - 6.9 * x42 * exp(-
      0.0010000000000000002 * power(x42, 3)) - 9.4 * x43 * exp(-
      0.010000000000000002 * sqr(x43)) - 4.3 * x44 * exp(-0.0010000000000000002
      * power(x44, 3)) - 8.8 * x45 * exp(-0.010000000000000002 * sqr(x45)) -
      6.7 * x46 * exp(-0.1 * x46) - 9.6 * x47 * exp(-0.010000000000000002 * sqr
      (x47)) - 6.6 * x48 * exp(-0.0010000000000000002 * power(x48, 3)) - 2.6 *
      x49 * exp(-0.1 * x49) - 2.1 * x50 * exp(-0.0010000000000000002 * power(
      x50, 3)) - 6.1 * x51 * exp(-0.1 * x51) =L= -651;
e4..  -9.3 * x2 * exp(-0.1 * x2) - 0.8 * x3 * exp(-0.1 * x3) - 6.7 * x4 * exp(
      -0.1 * x4) - 2.8 * x5 * exp(-0.1 * x5) - 8.7 * x6 * exp(-
      0.010000000000000002 * sqr(x6)) - 7.8 * x7 * exp(-0.010000000000000002 *
      sqr(x7)) - 2.2 * x8 * exp(-0.0010000000000000002 * power(x8, 3)) - 5.6 *
      x9 * exp(-0.1 * x9) - 6.6 * x10 * exp(-0.010000000000000002 * sqr(x10))
      - 4.8 * x11 * exp(-0.1 * x11) - x12 * exp(-0.1 * x12) - 1.9 * x13 * exp(
      -0.0010000000000000002 * power(x13, 3)) - 8.3 * x14 * exp(-0.1 * x14) - 6
      * x15 * exp(-0.0010000000000000002 * power(x15, 3)) - 3.7 * x16 * exp(-
      0.010000000000000002 * sqr(x16)) - 6.4 * x17 * exp(-0.010000000000000002
      * sqr(x17)) - 4.8 * x18 * exp(-0.010000000000000002 * sqr(x18)) - 9.2 *
      x19 * exp(-0.1 * x19) - 8.8 * x20 * exp(-0.0010000000000000002 * power(
      x20, 3)) - 7.3 * x21 * exp(-0.010000000000000002 * sqr(x21)) - 9.8 * x22
      * exp(-0.0010000000000000002 * power(x22, 3)) - 6.3 * x23 * exp(-
      0.0010000000000000002 * power(x23, 3)) - 1.9 * x24 * exp(-0.1 * x24) -
      1.3 * x25 * exp(-0.0010000000000000002 * power(x25, 3)) - 1.8 * x26 * exp
      (-0.010000000000000002 * sqr(x26)) - 5.5 * x27 * exp(-0.1 * x27) - 5.2 *
      x28 * exp(-0.010000000000000002 * sqr(x28)) - 5.1 * x29 * exp(-
      0.0010000000000000002 * power(x29, 3)) - 1.6 * x30 * exp(-
      0.010000000000000002 * sqr(x30)) - 0.6 * x31 * exp(-0.0010000000000000002
      * power(x31, 3)) - 9 * x32 * exp(-0.0010000000000000002 * power(x32, 3))
      - 4.3 * x33 * exp(-0.010000000000000002 * sqr(x33)) - 5.3 * x34 * exp(
      -0.1 * x34) - 1.8 * x35 * exp(-0.010000000000000002 * sqr(x35)) - 0.4 *
      x36 * exp(-0.1 * x36) - 7.8 * x37 * exp(-0.010000000000000002 * sqr(x37))
      - 4.2 * x38 * exp(-0.0010000000000000002 * power(x38, 3)) - 1.1 * x39 *
      exp(-0.0010000000000000002 * power(x39, 3)) - 8.3 * x40 * exp(-
      0.0010000000000000002 * power(x40, 3)) - 5.9 * x41 * exp(-
      0.0010000000000000002 * power(x41, 3)) - 4.7 * x42 * exp(-
      0.0010000000000000002 * power(x42, 3)) - 9 * x43 * exp(-0.1 * x43) - 6.5
      * x44 * exp(-0.1 * x44) - 3.6 * x45 * exp(-0.010000000000000002 * sqr(x45))
      - 3.6 * x46 * exp(-0.1 * x46) - 5.8 * x47 * exp(-0.010000000000000002 *
      sqr(x47)) - 0.2 * x48 * exp(-0.0010000000000000002 * power(x48, 3)) - 6.3
      * x49 * exp(-0.010000000000000002 * sqr(x49)) - 6 * x50 * exp(-0.1 * x50)
      - 8.3 * x51 * exp(-0.1 * x51) =L= -615;
e5..  -4.8 * x2 * exp(-0.0010000000000000002 * power(x2, 3)) - 0.9 * x3 * exp(
      -0.1 * x3) - 9.1 * x4 * exp(-0.010000000000000002 * sqr(x4)) - 4.6 * x5
      * exp(-0.010000000000000002 * sqr(x5)) - 6.7 * x6 * exp(-
      0.0010000000000000002 * power(x6, 3)) - 1.1 * x7 * exp(-0.1 * x7) - 7.6 *
      x8 * exp(-0.0010000000000000002 * power(x8, 3)) - 4.7 * x9 * exp(-
      0.010000000000000002 * sqr(x9)) - 8.6 * x10 * exp(-0.010000000000000002
      * sqr(x10)) - 4.6 * x11 * exp(-0.0010000000000000002 * power(x11, 3)) -
      8.5 * x12 * exp(-0.0010000000000000002 * power(x12, 3)) - 0.3 * x13 * exp
      (-0.0010000000000000002 * power(x13, 3)) - 3.8 * x14 * exp(-0.1 * x14) -
      1.9 * x15 * exp(-0.1 * x15) - 3.6 * x16 * exp(-0.1 * x16) - 5 * x17 * exp
      (-0.010000000000000002 * sqr(x17)) - 6.9 * x18 * exp(-
      0.010000000000000002 * sqr(x18)) - 5.7 * x19 * exp(-0.010000000000000002
      * sqr(x19)) - 0.2 * x20 * exp(-0.0010000000000000002 * power(x20, 3)) -
      2.5 * x21 * exp(-0.0010000000000000002 * power(x21, 3)) - 1.2 * x23 * exp
      (-0.010000000000000002 * sqr(x23)) - 3.9 * x24 * exp(-
      0.010000000000000002 * sqr(x24)) - 5.5 * x25 * exp(-0.010000000000000002
      * sqr(x25)) - 2.6 * x26 * exp(-0.1 * x26) - 5 * x27 * exp(-0.1 * x27) -
      2.1 * x28 * exp(-0.1 * x28) - 8.3 * x29 * exp(-0.1 * x29) - 1.1 * x30 *
      exp(-0.010000000000000002 * sqr(x30)) - 8.3 * x31 * exp(-0.1 * x31) - 9 *
      x32 * exp(-0.010000000000000002 * sqr(x32)) - 9.4 * x33 * exp(-
      0.010000000000000002 * sqr(x33)) - 8 * x34 * exp(-0.0010000000000000002
      * power(x34, 3)) - 1.3 * x35 * exp(-0.1 * x35) - 0.6 * x36 * exp(-
      0.0010000000000000002 * power(x36, 3)) - 5.5 * x37 * exp(-0.1 * x37) -
      7.6 * x38 * exp(-0.010000000000000002 * sqr(x38)) - 7.6 * x39 * exp(-
      0.0010000000000000002 * power(x39, 3)) - 3.2 * x40 * exp(-
      0.0010000000000000002 * power(x40, 3)) - 1.6 * x41 * exp(-
      0.0010000000000000002 * power(x41, 3)) - 4 * x42 * exp(-
      0.010000000000000002 * sqr(x42)) - 8.1 * x43 * exp(-0.1 * x43) - 1.3 *
      x44 * exp(-0.010000000000000002 * sqr(x44)) - 3.6 * x45 * exp(-0.1 * x45)
      - 1.8 * x46 * exp(-0.010000000000000002 * sqr(x46)) - 4.4 * x47 * exp(-
      0.010000000000000002 * sqr(x47)) - 5.4 * x48 * exp(-0.010000000000000002
      * sqr(x48)) - 3.7 * x49 * exp(-0.1 * x49) - 10 * x50 * exp(-0.1 * x50)
      - 0.5 * x51 * exp(-0.1 * x51) =L= -788;
e6..  -7.5 * x2 * exp(-0.1 * x2) - 5.7 * x3 * exp(-0.010000000000000002 * sqr(
      x3)) - 7.9 * x4 * exp(-0.0010000000000000002 * power(x4, 3)) - 4 * x5 *
      exp(-0.0010000000000000002 * power(x5, 3)) - 8.9 * x6 * exp(-
      0.010000000000000002 * sqr(x6)) - 2.1 * x7 * exp(-0.010000000000000002 *
      sqr(x7)) - 6.4 * x8 * exp(-0.1 * x8) - 9 * x9 * exp(-0.1 * x9) - 2.4 *
      x10 * exp(-0.010000000000000002 * sqr(x10)) - 6.6 * x11 * exp(-
      0.010000000000000002 * sqr(x11)) - 5.4 * x12 * exp(-0.0010000000000000002
      * power(x12, 3)) - 7.3 * x13 * exp(-0.010000000000000002 * sqr(x13)) -
      5.9 * x14 * exp(-0.010000000000000002 * sqr(x14)) - 0.7 * x15 * exp(-0.1
      * x15) - 7.7 * x16 * exp(-0.0010000000000000002 * power(x16, 3)) - 6.8 *
      x17 * exp(-0.0010000000000000002 * power(x17, 3)) - 1.7 * x18 * exp(-
      0.0010000000000000002 * power(x18, 3)) - 5.5 * x19 * exp(-0.1 * x19) -
      9.3 * x20 * exp(-0.0010000000000000002 * power(x20, 3)) - 7.2 * x21 * exp
      (-0.010000000000000002 * sqr(x21)) - 8.5 * x22 * exp(-0.1 * x22) - 8.6 *
      x23 * exp(-0.0010000000000000002 * power(x23, 3)) - 0.1 * x24 * exp(-
      0.010000000000000002 * sqr(x24)) - 3.1 * x25 * exp(-0.010000000000000002
      * sqr(x25)) - 3.5 * x26 * exp(-0.010000000000000002 * sqr(x26)) - 7.8 *
      x27 * exp(-0.0010000000000000002 * power(x27, 3)) - 8.5 * x28 * exp(-
      0.010000000000000002 * sqr(x28)) - 0.9 * x29 * exp(-0.0010000000000000002
      * power(x29, 3)) - 7.9 * x30 * exp(-0.0010000000000000002 * power(x30, 3))
      - 8 * x31 * exp(-0.0010000000000000002 * power(x31, 3)) - 2.5 * x32 *
      exp(-0.010000000000000002 * sqr(x32)) - 8.1 * x33 * exp(-
      0.010000000000000002 * sqr(x33)) - 6 * x34 * exp(-0.010000000000000002 *
      sqr(x34)) - 5.8 * x35 * exp(-0.010000000000000002 * sqr(x35)) - 0.7 * x36
      * exp(-0.1 * x36) - 2.1 * x37 * exp(-0.0010000000000000002 * power(x37,
      3)) - 9.6 * x38 * exp(-0.010000000000000002 * sqr(x38)) - 9.3 * x39 * exp
      (-0.1 * x39) - 7.1 * x40 * exp(-0.1 * x40) - 4.7 * x41 * exp(-
      0.0010000000000000002 * power(x41, 3)) - 8.7 * x42 * exp(-0.1 * x42) -
      9.3 * x43 * exp(-0.010000000000000002 * sqr(x43)) - 1.5 * x44 * exp(-
      0.010000000000000002 * sqr(x44)) - 1.4 * x45 * exp(-0.010000000000000002
      * sqr(x45)) - 8 * x46 * exp(-0.010000000000000002 * sqr(x46)) - 1.8 *
      x47 * exp(-0.0010000000000000002 * power(x47, 3)) - 6.2 * x48 * exp(-
      0.010000000000000002 * sqr(x48)) - 6.8 * x49 * exp(-0.010000000000000002
      * sqr(x49)) - 8.8 * x50 * exp(-0.010000000000000002 * sqr(x50)) - 2.5 *
      x51 * exp(-0.010000000000000002 * sqr(x51)) =L= -984;

* set non-default bounds
x2.lo = 0; x2.up = 10;
x3.lo = 0; x3.up = 10;
x4.lo = 0; x4.up = 10;
x5.lo = 0; x5.up = 10;
x6.lo = 0; x6.up = 10;
x7.lo = 0; x7.up = 10;
x8.lo = 0; x8.up = 10;
x9.lo = 0; x9.up = 10;
x10.lo = 0; x10.up = 10;
x11.lo = 0; x11.up = 10;
x12.lo = 0; x12.up = 10;
x13.lo = 0; x13.up = 10;
x14.lo = 0; x14.up = 10;
x15.lo = 0; x15.up = 10;
x16.lo = 0; x16.up = 10;
x17.lo = 0; x17.up = 10;
x18.lo = 0; x18.up = 10;
x19.lo = 0; x19.up = 10;
x20.lo = 0; x20.up = 10;
x21.lo = 0; x21.up = 10;
x22.lo = 0; x22.up = 10;
x23.lo = 0; x23.up = 10;
x24.lo = 0; x24.up = 10;
x25.lo = 0; x25.up = 10;
x26.lo = 0; x26.up = 10;
x27.lo = 0; x27.up = 10;
x28.lo = 0; x28.up = 10;
x29.lo = 0; x29.up = 10;
x30.lo = 0; x30.up = 10;
x31.lo = 0; x31.up = 10;
x32.lo = 0; x32.up = 10;
x33.lo = 0; x33.up = 10;
x34.lo = 0; x34.up = 10;
x35.lo = 0; x35.up = 10;
x36.lo = 0; x36.up = 10;
x37.lo = 0; x37.up = 10;
x38.lo = 0; x38.up = 10;
x39.lo = 0; x39.up = 10;
x40.lo = 0; x40.up = 10;
x41.lo = 0; x41.up = 10;
x42.lo = 0; x42.up = 10;
x43.lo = 0; x43.up = 10;
x44.lo = 0; x44.up = 10;
x45.lo = 0; x45.up = 10;
x46.lo = 0; x46.up = 10;
x47.lo = 0; x47.up = 10;
x48.lo = 0; x48.up = 10;
x49.lo = 0; x49.up = 10;
x50.lo = 0; x50.up = 10;
x51.lo = 0; x51.up = 10;

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% maximizing objvar;


Last updated: 2024-08-26 Git hash: 6cc1607f
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