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Hybrid MIP-CP problem solving: sequential solving

Description
The idea of this example is to use a Constraint Programming (CP) model to preprocess data for an LP problem. The constraint propagation performed by the CP solver tightens the bounds on certain decision variables.
  • solving a sequence of CP subproblems
  • data exchange between several models via shared memory
Further explanation of this example: Xpress Whitepaper 'Hybrid MIP/CP solving', Section 'Using CP propagation as preprocessor'. The example problem, namely planning the construction of a stadium, is described in the book 'Applications of optimization with Xpress-MP'.

b1stadium_h.zip[download all files]

Source Files
By clicking on a file name, a preview is opened at the bottom of this page.
b1stadium_ka.mos[download]
b1stadium_main.mos[download]
b1stadium_sub.mos[download]

Data Files
b1stadium.dat[download]




b1stadium.dat

! Data file for `b1stadium.mos'

ARC: [(1 2) 1
      (2 3) 1  (2 4) 1  (2 14) 1
      (3 5) 1
      (4 6) 1  (4 7) 1  (4 9) 1  (4 10) 1  (4 15) 1
      (5 6) 1
      (6 8) 1  (6 9) 1  (6 11) 1
      (7 13) 1
      (8 16) 1
      (9 12) 1
     (10 19) 1
     (11 16) 1
     (12 17) 1
     (13 19) 1
     (14 15) 1  (14 16) 1
     (15 19) 1
     (16 19) 1
     (17 18) 1
     (18 19) 1 ]
     
COST: [0 30 26 12 17 15  8  0 42 21 18  0  0 22 12  6 16  0  0]

DUR:  [2 16  9  8 10  6  2  2  9  5  3  2  1  7  4  3  9  1  0]

MAXW: [0  3  1  2  2  1  1  0  2  1  1  0  0  2  2  1  3  0  0]

BONUS: 30
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