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Mining and process industries

Description
Problem name and type, featuresDifficulty
A‑1 Production of alloys: Blending problem *
formulation of blending constraints; data with numerical indices, solution printout, if-then, getsol
A‑2 Animal food production: Blending problem *
formulation of blending constraints; data with string indices, as, formatted solution printout, use of getsol with linear expressions, strfmt
A‑3 Refinery : Blending problem **
formulation of blending constraints; sparse data with string indices, dynamic initialization, dynamic arrays, finalize, create, union of sets
A‑4 Cane sugar production : Minimum cost flow (in a bipartite graph) *
ceil, is_binary
A‑5 Opencast mining: Minimum cost flow **
encoding of arcs, solving LP-relaxation only
A‑6 Production of electricity: Dispatch problem **
inline if, is_integer


Further explanation of this example: 'Applications of optimization with Xpress-MP', Chapter 6: Mining and process industries (blending problems)

mosel_app_1.zip[download all files]

Source Files

Data Files





a1alloy.dat

! Data file for `a1alloy.mos'

P: [2.5   0 1.3                              ! Raw material composition
    3   0 0.8 
    0 0.3   0
    0  90   0
    0  96   4
    0 0.4 1.2
    0 0.6   0] 

PMIN: [2 0.4 1.2]
PMAX: [3 0.6 1.65]                           ! Min. & max. requirements
  
AVAIL: [400 300 600 500 200 300 250]         ! Raw material availabilities

COST: [200 250 150 220 240 200 165]          ! Raw material costs

DEM: 500                                     ! Amount of steel to produce

NAMES: ["iron 1" "iron 2" "iron 3" "copper 1" "copper 2" 
        "aluminum 1" "aluminum 2"]

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