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Blending ores

Description
Several ores are blended to a final product that must have a certain quality ('grade'). We wish to determine the quantity of every ore to be used in the blend with the objective to maximize the total profit (calculated as sales revenues - raw material cost).
  • simple LP problem
  • data in model or input from file
  • bounds on variables
Further explanation of this example: 'Mosel User Guide', Section 2.2 'A blending example'; 'Applications of optimization with Xpress-MP', Section 2.7 'Blending constraints'. Similar problems: Section 6.1 'Production of alloys', Section 6.2 'Animal food production', Section 6.3 'Refinery'

blendinggr.zip[download all files]

Source Files

Data Files





blend.mos

(!*******************************************************
  * Mosel Example Problems                              *
  * ======================                              *
  *                                                     *
  * file blend.mos                                      *
  * ``````````````                                      *
  * Example for the use of the Mosel language           *
  * (Blending problem)                                  *
  *                                                     *
  * Reading data from file.                             *
  *                                                     *
  * (c) 2008 Fair Isaac Corporation                     *
  *     author: S. Heipcke, 2001, rev. Feb. 2010        *
  *******************************************************!)

model Blend                    ! Start a new model

uses "mmxprs"                  ! Load the optimizer library

declarations
 ROres = 1..2                  ! Range of Ores
 REV = 125                     ! Unit revenue of product
 MINGRADE = 4                  ! Min permitted grade of product
 MAXGRADE = 5                  ! Max permitted grade of product
 COST: array(ROres) of real    ! Unit cost of ores
 AVAIL: array(ROres) of real   ! Availability of ores
 GRADE: array(ROres) of real   ! Grade of ores (measured per unit of mass)

 x: array(ROres) of mpvar      ! Quantities of ores used
end-declarations

                               ! Read data from file
initializations from 'Data/blend.dat'
 COST
 AVAIL
 GRADE
end-initializations
                               ! Objective: maximize total profit
 Profit:= sum(o in ROres) (REV-COST(o))* x(o)  

                               ! Lower and upper bounds on ore quality
 LoGrade:= sum(o in ROres) (GRADE(o)-MINGRADE) * x(o) >= 0
 UpGrade:= sum(o in ROres) (MAXGRADE-GRADE(o)) * x(o) >= 0 

                               ! Set upper bounds on variables
 forall(o in ROres) x(o) <= AVAIL(o)
  
 maximize(Profit)              ! Solve the LP-problem

                               ! Print out the solution
 writeln("Solution:\n Objective: ", getobjval)
 forall(o in ROres)  writeln(" x(" + o + "): ", x(o).sol)
 writeln("Grade: ", 
         (sum(o in ROres) GRADE(o)*x(o).sol) / sum(o in ROres) x(o).sol, 
         "  [min,max]: [", MINGRADE, ",", MAXGRADE, "]")

end-model

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