The McDonald's Diet Problem A Case Study in Optimization Using AMPL

2. VARIETY IS THE SPICE OF LIFE

Here's the original diet solution again. Optimal solutions to linear programs tend to look like this: do a lot of a few things. This could easily get boring.

   stretto% ampl
   
   ampl: model diet1.mod;
   ampl: data diet1.dat;
   
   ampl data: solve;
   MINOS 5.4: ignoring integrality of 9 variables
   MINOS 5.4: optimal solution found.
   8 iterations, objective 14.8557377
   
   ampl: display Buy;
   
   Buy [*] :=
   'Quarter Pounder w/ Cheese'  4.38525
     'McLean Deluxe w/ Cheese'  0
                     'Big Mac'  0
                  Filet-O-Fish  0
           'McGrilled Chicken'  0
                'Fries, small'  6.14754
            'Sausage McMuffin'  0
              '1% Lowfat Milk'  3.42213
                'Orange Juice'  0
   ;
   
   ampl: display n_min,Diet.body,n_max;
   
   :        n_min  Diet.body    n_max      :=
   Cal       2000   3965.37    Infinity
   Carbo      350    350            375
   Protein     55    172.029   Infinity
   VitA       100    100       Infinity
   VitC       100    132.213   Infinity
   Calc       100    234.221   Infinity
   Iron       100    100       Infinity
   ;

In the interest of variety, we can say that the diet should not involve buying more than two of any one item. Then we get indeed a much more varied solution, and as a bonus it has somewhat fewer calories. On the other hand, the cost goes up from $14.85 to $16.76. 

   ampl: let {j in FOOD} f_max[j] := 2;
   
   ampl: solve;
   MINOS 5.4: ignoring integrality of 9 variables
   MINOS 5.4: optimal solution found.
   6 iterations, objective 16.76576923
   
   ampl: display Buy;
   
   Buy [*] :=
   'Quarter Pounder w/ Cheese'  2
     'McLean Deluxe w/ Cheese'  2
                     'Big Mac'  2
                  Filet-O-Fish  0
           'McGrilled Chicken'  0
                'Fries, small'  1.42308
            'Sausage McMuffin'  1
              '1% Lowfat Milk'  2
                'Orange Juice'  2
   ;
   
   ampl: display n_min,Diet.body,n_max;
   
   :        n_min  Diet.body    n_max      :=
   Cal       2000   3798.08    Infinity
   Carbo      350    350            375
   Protein     55    193.269   Infinity
   VitA       100    100       Infinity
   VitC       100    305.346   Infinity
   Calc       100    234       Infinity
   Iron       100    141.846   Infinity
   ;

How low can we reduce the calories, now that we've added the variety constraint? Only to 3488 -- compared to under 2500 before. Also the cost of this diet, about $17.25, is about 50 cents higher than the minimum-calorie diet without the variety restriction. Still, the diet is significantly different; no Big Macs, for one thing.

   ampl: objective Nutr_Amt["Cal"];
   
   ampl: solve;
   MINOS 5.4: ignoring integrality of 9 variables
   MINOS 5.4: optimal solution found.
   6 iterations, objective 3488.286853
   
   ampl: display Total_Cost;
   Total_Cost = 17.2484
   
   ampl: display Buy;
   
   Buy [*] :=
   'Quarter Pounder w/ Cheese'  1.95219
     'McLean Deluxe w/ Cheese'  2
                     'Big Mac'  0
                  Filet-O-Fish  0.358566
           'McGrilled Chicken'  2
                'Fries, small'  2
            'Sausage McMuffin'  0
              '1% Lowfat Milk'  2
                'Orange Juice'  2
   ;
   
   ampl: display n_min,Diet.body,n_max;
   :        n_min  Diet.body    n_max      :=
   Cal       2000   3488.29    Infinity
   Carbo      350    350            375
   Protein     55    195.681   Infinity
   VitA       100    100       Infinity
   VitC       100    339.713   Infinity
   Calc       100    197.944   Infinity
   Iron       100    106.629   Infinity
   ;
   
   ampl:


Comments or questions?
Write to info@ampl.com or use our comment form.

Return to the AMPL examples page.

Return to the AMPL home page.

LAST MODIFIED 27 MARCH 1996 BY 4er.