| The OPTMODEL Procedure |
| The Rosenbrock Problem |
You can use parameters to produce a clear formulation of a problem. Consider the Rosenbrock problem:
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where
is a parameter (constant),
and
are optimization variables (whose values are to be determined), and
is an objective function.
Here is a PROC OPTMODEL program that solves the Rosenbrock problem:
proc optmodel;
number alpha = 100; /* declare parameter */
var x {1..2}; /* declare variables */
/* objective function */
min f = alpha*(x[2] - x[1]**2)**2 +
(1 - x[1])**2;
/* now run the solver */
solve;
print x;
quit;
The PROC OPTMODEL output is shown in Figure 8.3.
| Problem Summary | |
|---|---|
| Objective Sense | Minimization |
| Objective Function | f |
| Objective Type | Nonlinear |
| Number of Variables | 2 |
| Bounded Above | 0 |
| Bounded Below | 0 |
| Bounded Below and Above | 0 |
| Free | 2 |
| Fixed | 0 |
| Number of Constraints | 0 |
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