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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





a5mine.dat

! Data file for 'a5mine.mos'

COST: [100  100  100  100  100  100  100 100 
           1000  200  200  200  200 1000
                1000 1000  300 1000]
                
VALUE: [(1) 200 (7) 300 (10) 500 (12) 200 (17) 1000 (18) 1200] 

ARC: [(9 1) 1 2 3 (10 1) 2 3 4 (11 1) 3 4 5 (12 1) 4 5 6 (13 1) 5 6 7 (14 1) 6 7 8
       (15 1) 9 10 11 (16 1) 10 11 12 (17 1) 11 12 13 (18 1) 12 13 14]

WEIGHT: 10000

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