(!*********************************************************************
   Mosel Example Problems
   ======================

   file simple2.mos
   ````````````````
   Simple LP problem 
   
     Example solution to exercise 2.3 in section 2.13 of
     J. Kallrath: Business Optimization Using Mathematical Programming -
     An Introduction with Case Studies and Solutions in Various Algebraic 
     Modeling Languages. 2nd edition, Springer Nature, Cham, 2021 

   author: S. Heipcke, June 2018

   (c) Copyright 2020 Fair Isaac Corporation
  
    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.
    You may obtain a copy of the License at
 
       http://www.apache.org/licenses/LICENSE-2.0
 
    Unless required by applicable law or agreed to in writing, software
    distributed under the License is distributed on an "AS IS" BASIS,
    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    See the License for the specific language governing permissions and
    limitations under the License.

*********************************************************************!)

model 'simple2'
  uses "mmxprs"

  declarations
    RV=1..4                   ! Set of variables
    RC=1..3                   ! Set of constraints
    C: array(RV) of real      ! Objective coefficients - profits
    A: array(RC,RV) of real   ! Constraint coefficients - resources
    B: array(RC) of real      ! RHS values - resource limits
    x: array(RV) of mpvar     ! The decision variables
  end-declarations

  C::[15,6,9,2]
  A::[10,5,25,3,
      12,4,12,1,
      7,0,0,1]
  B::[100,96,70]

  Profit:= sum(j in RV) C(j) * x(j)    ! Objective - total profit

  forall(i in RC)
    Con(i):=sum(j in RV) A(i,j) * x(j)<= B(i)  ! Constraints

 ! Solve the problem
  maximise(Profit)
  writeln("Solution: ", getobjval)
  forall(j in RV) writeln("  x", j, ":", x(j).sol)
end-model