If you are using SAS University Edition, then you have access to SAS/IML, which supports linear programming (LP) and mixed-integer LP. . Use the MILPSOLVE subroutine, as follows
/* Problem: x is a vector of integers 0 <= x[i] <= 10
maximize c*x = 3*x1 + 5*x2
subject to
A*x SYMBOL b
where SYMBOL is a vector of symbols that indicate <=, =, or >=
*/
proc optmodel;
var x{i in 1..2} integer >= 0;
max z = 3*x[1] + 5*x[2];
con c1: 3*x[1] + -2*x[2] <= 10;
con c2: 5*x[1] + 10*x[2] <= 56;
solve with milp;
print x;
quit;
proc iml;
/* information about variables (row of column, doesn't matter) */
colType = {I, I}; /* variables are integers */
LowerB = {0, 0}; /* lower bound contraints on x */
UpperB = {10,10}; /* upper bound contraints on x */
/* objective function */
c = {3 5}; /* vector for objective function c*x */
/* linear constraints */
A = {3 -2, /* matrix of contraint coefficients */
5 10};
b = {10, /* RHS of constraint eqns (column vector) */
56};
/* specify symbols for constraints:
'L' for less than or equal
'E' for equal
'G' for greater than or equal */
LEG = {L, L};
/* control vector for optimization */
ctrl = {-1, /* maximize objective */
1}; /* print level */
CALL MILPSOLVE(rc, objVal, result, relgap, /* output variables */
c, A, b, /* objective and linear constraints */
ctrl, /* control vector */
coltype, LEG, /*range*/, LowerB, UpperB);
print rc objVal relgap, result[rowname={x1 x2}];
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