The source code and dockerfile for the GSW2024 AI Lab.
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  1. /* FCTP, Fixed-Charge Transportation Problem */
  2. /* Written in GNU MathProg by Andrew Makhorin <mao@gnu.org> */
  3. /* The Fixed-Charge Transportation Problem (FCTP) is obtained from
  4. classical transportation problem by imposing a fixed cost on each
  5. transportation link if there is a positive flow on that link. */
  6. param m, integer, > 0;
  7. /* number of sources */
  8. param n, integer, > 0;
  9. /* number of customers */
  10. set I := 1..m;
  11. /* set of sources */
  12. set J := 1..n;
  13. /* set of customers */
  14. param supply{i in I}, >= 0;
  15. /* supply at source i */
  16. param demand{j in J}, >= 0;
  17. /* demand at customer j */
  18. param varcost{i in I, j in J}, >= 0;
  19. /* variable cost (a cost per one unit shipped from i to j) */
  20. param fixcost{i in I, j in J}, >= 0;
  21. /* fixed cost (a cost for shipping any amount from i to j) */
  22. var x{i in I, j in J}, >= 0;
  23. /* amount shipped from source i to customer j */
  24. s.t. f{i in I}: sum{j in J} x[i,j] = supply[i];
  25. /* observe supply at source i */
  26. s.t. g{j in J}: sum{i in I} x[i,j] = demand[j];
  27. /* satisfy demand at customer j */
  28. var y{i in I, j in J}, binary;
  29. /* y[i,j] = 1 means some amount is shipped from i to j */
  30. s.t. h{i in I, j in J}: x[i,j] <= min(supply[i], demand[j]) * y[i,j];
  31. /* if y[i,j] is 0, force x[i,j] to be 0 (may note that supply[i] and
  32. demand[j] are implicit upper bounds for x[i,j] as follows from the
  33. constraints f[i] and g[j]) */
  34. minimize cost: sum{i in I, j in J} varcost[i,j] * x[i,j] +
  35. sum{i in I, j in J} fixcost[i,j] * y[i,j];
  36. /* total transportation costs */
  37. data;
  38. /* These data correspond to the instance bal8x12 from [Balinski]. */
  39. /* The optimal solution is 471.55 */
  40. param m := 8;
  41. param n := 12;
  42. param supply := 1 15.00, 2 20.00, 3 45.00, 4 35.00,
  43. 5 25.00, 6 35.00, 7 10.00, 8 25.00;
  44. param demand := 1 20.00, 2 15.00, 3 20.00, 4 15.00,
  45. 5 5.00, 6 20.00, 7 30.00, 8 10.00,
  46. 9 35.00, 10 25.00, 11 10.00, 12 5.00;
  47. param varcost
  48. : 1 2 3 4 5 6 7 8 9 10 11 12 :=
  49. 1 0.69 0.64 0.71 0.79 1.70 2.83 2.02 5.64 5.94 5.94 5.94 7.68
  50. 2 1.01 0.75 0.88 0.59 1.50 2.63 2.26 5.64 5.85 5.62 5.85 4.94
  51. 3 1.05 1.06 1.08 0.64 1.22 2.37 1.66 5.64 5.91 5.62 5.91 4.94
  52. 4 1.94 1.50 1.56 1.22 1.98 1.98 1.36 6.99 6.99 6.99 6.99 3.68
  53. 5 1.61 1.40 1.61 1.33 1.68 2.83 1.54 4.26 4.26 4.26 4.26 2.99
  54. 6 5.29 5.94 6.08 5.29 5.96 6.77 5.08 0.31 0.21 0.17 0.31 1.53
  55. 7 5.29 5.94 6.08 5.29 5.96 6.77 5.08 0.55 0.35 0.40 0.19 1.53
  56. 8 5.29 6.08 6.08 5.29 5.96 6.45 5.08 2.43 2.30 2.33 1.81 2.50 ;
  57. param fixcost
  58. : 1 2 3 4 5 6 7 8 9 10 11 12 :=
  59. 1 11.0 16.0 18.0 17.0 10.0 20.0 17.0 13.0 15.0 12.0 14.0 14.0
  60. 2 14.0 17.0 17.0 13.0 15.0 13.0 16.0 11.0 20.0 11.0 15.0 10.0
  61. 3 12.0 13.0 20.0 17.0 13.0 15.0 16.0 13.0 12.0 13.0 10.0 18.0
  62. 4 16.0 19.0 16.0 11.0 15.0 12.0 18.0 12.0 18.0 13.0 13.0 14.0
  63. 5 19.0 18.0 15.0 16.0 12.0 14.0 20.0 19.0 11.0 17.0 16.0 18.0
  64. 6 13.0 20.0 20.0 17.0 15.0 12.0 14.0 11.0 12.0 19.0 15.0 16.0
  65. 7 11.0 12.0 15.0 10.0 17.0 11.0 11.0 16.0 10.0 18.0 17.0 12.0
  66. 8 17.0 10.0 20.0 12.0 17.0 20.0 16.0 15.0 10.0 12.0 16.0 18.0 ;
  67. end;