The Nonlinear Programming Solver

Some NLP problems contain many local minima. By default, the NLP solver converges to a single local minimum. However, the NLP solver can search the feasible region for other local minima. After it completes the search, it returns the point where the objective function achieves its minimum value. (This point might not be a local minimum; see the SOLTYPE= option for more details.) Consider the following example, taken from Hock and Schittkowski (1981):

The following statements call the NLP solver to search the feasible region for different local minima. The PERFORMANCE statement requests that the multistart algorithm use up to four threads. The SEED= option is specified for reproducibility, but it is not required in running the multistart algorithm.

proc optmodel;
   var x{i in 1..5} >= -5 <= 5 init -2;

   min f=(x[1] - 1)^2 + (x[1] - x[2])^2 + (x[2] - x[3])^3 +
         (x[3] - x[4])^4 + (x[4] - x[5])^4;

   con g1: x[1] + x[2]^2 + x[3]^3 =  2 + 3*sqrt(2);
   con g2: x[2] + x[4]   - x[3]^2 = -2 + 2*sqrt(2);
   con g3: x[1]*x[5] = 2;

   performance nthreads=4;
   solve with nlp/multistart=(maxstarts=10) seed=1234;
   print x.msinit x;
quit;

The PRINT statement prints the starting point (x.msinit) that led to the best local solution and the best local solution (x) that the NLP solver found in multistart mode. The SAS log is shown in Output 10.5.1.

The first column in the log indicates the index of the current starting point. An additional indicator (*) can appear after the index to provide more information about the optimization run that started from the current point. For more information, see the section Iteration Log for Multistart. The second column records the best objective that has been found so far. Columns 3 to 6 report the objective value, optimality error, infeasibility, and number of iterations that the local solver returned when it was started from the current starting point. Finally, the last column records the status of the local solver—namely, whether it was able to converge to a local optimum from the current starting point.

The summaries and solution are shown in Output 10.5.2. Note that the best local solution was found by starting the local solver from a point at x.msinit.

Alternatively, the following SAS statements show how you can add the NODES= option in the PERFORMANCE statement to run this example in distributed mode.

Note: SAS High-Performance Optimization software must be installed before you can invoke the MULTISTART option in distributed mode.

proc optmodel;
   var x{i in 1..5} >= -5 <= 5 init -2;

   min f=(x[1] - 1)^2 + (x[1] - x[2])^2 + (x[2] - x[3])^3 +
         (x[3] - x[4])^4 + (x[4] - x[5])^4;

   con g1: x[1] + x[2]^2 + x[3]^3 =  2 + 3*sqrt(2);
   con g2: x[2] + x[4]   - x[3]^2 = -2 + 2*sqrt(2);
   con g3: x[1]*x[5] = 2;

   performance nodes=4 nthreads=4;
   solve with nlp/multistart=(maxstarts=10) seed=1234;
   print x;
quit;

The SAS log is displayed in Output 10.5.3.

Output 10.5.4 shows the summaries and solution. Note that the "Performance Information" table shows that four computing nodes with four threads on each node are used in distributed mode.