Diet Problem (lpsol1)
/***************************************************************/
/* */
/* S A S S A M P L E L I B R A R Y */
/* */
/* NAME: lpsol1 */
/* TITLE: Diet Problem (lpsol1) */
/* PRODUCT: OR */
/* SYSTEM: ALL */
/* KEYS: OR */
/* PROCS: OPTMODEL */
/* DATA: */
/* */
/* SUPPORT: UPDATE: */
/* REF: */
/* MISC: Example 1 from the Linear Programming Solver */
/* chapter of Mathematical Programming. */
/* */
/***************************************************************/
data fooddata;
infile datalines;
input name $ cost prot fat carb cal;
datalines;
Bread 2 4 1 15 90
Milk 3.5 8 5 11.7 120
Cheese 8 7 9 0.4 106
Potato 1.5 1.3 0.1 22.6 97
Fish 11 8 7 0 130
Yogurt 1 9.2 1 17 180
;
proc optmodel;
/* declare index set */
set<str> FOOD;
/* declare variables */
var diet{FOOD} >= 0;
/* objective function */
num cost{FOOD};
min f=sum{i in FOOD}cost[i]*diet[i];
/* constraints */
num prot{FOOD};
num fat{FOOD};
num carb{FOOD};
num cal{FOOD};
num min_cal, max_prot, min_carb, min_fat;
con cal_con: sum{i in FOOD}cal[i]*diet[i] >= 300;
con prot_con: sum{i in FOOD}prot[i]*diet[i] <= 10;
con carb_con: sum{i in FOOD}carb[i]*diet[i] >= 10;
con fat_con: sum{i in FOOD}fat[i]*diet[i] >= 8;
/* read parameters */
read data fooddata into FOOD=[name] cost prot fat carb cal;
/* bounds on variables */
diet['Fish'].lb = 0.5;
diet['Milk'].ub = 1.0;
/* solve and print the optimal solution */
solve with lp/logfreq=1; /* print each iteration to log */
print diet;
quit;