The OPTMODEL Procedure

The Rosenbrock Problem

You can use parameters to produce a clear formulation of a problem. Consider the Rosenbrock problem,

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 10.3.

Figure 10.3: Rosenbrock Function Results

The OPTMODEL Procedure

Problem Summary
Objective SenseMinimization
Objective Functionf
Objective TypeNonlinear
  
Number of Variables2
Bounded Above0
Bounded Below0
Bounded Below and Above0
Free2
Fixed0
  
Number of Constraints0

Solution Summary
SolverNLP
AlgorithmInterior Point
Objective Functionf
Solution StatusOptimal
Objective Value8.204873E-23
  
Optimality Error9.704881E-11
Infeasibility0
  
Iterations14
Presolve Time0.00
Solution Time0.07

[1]x
11
21


Last updated: June 14, 2018