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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





a3refine.dat

! Data file for 'a3refine.mos'

DEM : [(butane) 20000 (petrol) 40000 (diesel) 30000 (heating) 42000]

OCT: [(petbutane) 120 (reformate) 100 (petcrknaphtha) 74]
VAP: [(petbutane)  60 (reformate) 2.6 (petcrknaphtha) 4.1]
VOL: [(petbutane) 105 (reformate) 3   (petcrknaphtha) 12]

SULF: [(dslgasoil) 0.03 (dslcrknaphtha) 0.12 (dslcrkgasoil) 0.76]

AVAIL: [(crude1) 250000 (crude2) 500000]

REF: [(refbutane) 0.15 (reformate) 0.85]
CRACK: [(crknaphtha) 0.40 (crkgasoil) 0.35]

DIST: [(crude1 distbutane) 0.03 (crude1 naphtha) 0.15 (crude1 gasoil) 0.40 
      (crude1 residue) 0.15
      (crude2 distbutane) 0.05 (crude2 naphtha) 0.20 (crude2 gasoil) 0.35 
      (crude2 residue) 0.10] 

COST: [(crude1) 2.1 (crude2) 2.1 
       (distbutane) 0 (naphtha) 4.18 (residue) 0.6 (gasoil) 2.04 ]

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