The first several PROC OPTMODEL statements are straightforward declarations of index sets, parameters, and variables:

proc optmodel;
   set <str> MINES;
   num cost {MINES};
   num extract_ub {MINES};
   num quality {MINES};
   read data mine_data into MINES=[mine] cost extract_ub quality;

   set YEARS;
   num quality_required {YEARS};
   read data year_data into YEARS=[year] quality_required;

   var IsOpen {MINES, YEARS} binary;
   var IsWorked {MINES, YEARS} binary;
   var Extract {mine in MINES, YEARS} >= 0 <= extract_ub[mine];

The following IMPVAR statement declares ExtractedPerYear as an implicit variable. Using the IMPVAR statement is an alternative to using a VAR statement and an additional constraint.

   impvar ExtractedPerYear {year in YEARS} 
      = sum {mine in MINES} Extract[mine,year];

The following NUM statement uses a formula to compute the discount (shown in Figure 8.1) that is used in the objective function:

   num discount {year in YEARS} = 1 / (1 + &discount_rate)^(year - 1);
   print discount;
   
   impvar TotalRevenue = 
      &revenue_per_ton * sum {year in YEARS} discount[year] * 
         ExtractedPerYear[year];
   impvar TotalCost = 
      sum {mine in MINES, year in YEARS} discount[year] * cost[mine] * 
         IsOpen[mine,year];
   max TotalProfit = TotalRevenue - TotalCost;

The following Link constraint enforces the rule that implies that (as in Chapter 3):

   con Link {mine in MINES, year in YEARS}:
      Extract[mine,year] <= Extract[mine,year].ub * IsWorked[mine,year];

The following Cardinality constraint enforces the limit on number of mines worked per year:

   con Cardinality {year in YEARS}:
      sum {mine in MINES} IsWorked[mine,year] <= &max_num_worked_per_year;

The following Worked_implies_open constraint enforces the rule that implies that :

   con Worked_implies_open {mine in MINES, year in YEARS}:
      IsWorked[mine,year] <= IsOpen[mine,year];

The following Continuity constraint enforces the rule that implies that :

   con Continuity {mine in MINES, year in YEARS diff {1}}:
      IsOpen[mine,year] <= IsOpen[mine,year-1];

As expressed on , the quality of the blended ore for each year is a ratio of linear functions of the decision variables. The following CON statement linearizes the nonlinear ratio constraint by clearing the denominator:

   con Quality_con {year in YEARS}:
      sum {mine in MINES} quality[mine] * Extract[mine,year] 
    = quality_required[year] * ExtractedPerYear[year];

By using the .sol suffix, the numeric parameter quality_sol computes the quality of the blended ore from the optimal decision variable values that are returned by the solver:

   num quality_sol {year in YEARS} = 
      (sum {mine in MINES} quality[mine] * Extract[mine,year].sol) / 
         ExtractedPerYear[year].sol;

   solve;
   print IsOpen IsWorked Extract;
   print ExtractedPerYear quality_sol quality_required;
   create data sol_data1 from [mine year] IsOpen IsWorked Extract;
   create data sol_data2 from [year] ExtractedPerYear;
quit;

Figure 8.2 shows the output from the mixed integer linear programming solver. The values of quality_sol and quality_required agree, as enforced by the Quality_con constraint.