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Details of the OPTEX Procedure 
See OPTEX4 in the SAS/QC Sample Library 
This example is a continuation of Example 24.4.
A wellchosen initial design can speed up the search procedure, as illustrated in Example 24.2. Another way to speed up the search is to reduce the candidate set. The following statements generate the optimal design with a fast, sequential search and then use the FREQ procedure to examine the frequency of different factor levels in the final design:
proc optex data=a seed=33805 noprint; model afegrsa@2 af*af egr*egr sa*sa; generate n=50 method=sequential; output out=b; proc freq; table af egr sa / nocum; run;Output 24.5.1: Factor Level Frequencies for Sequential Design
From Output 24.5.1, it is evident that most of the factor values lie in the middle or at the extremes of their respective ranges. This suggests looking for an optimal design with a candidate set that includes only those points in which the factors have values in the middle or at the extremes of their respective ranges. The following statements illustrate this approach (see Output 24.5.2):
proc plan; factors af=4 ordered egr=4 ordered sa=4 ordered / noprint; output out=a af nvals=( 15, 16, 17, 18) egr nvals=(.020,.377,.566,1.117) sa nvals=( 10, 28, 34, 52); proc optex seed=61552; model afegrsa@2 af*af egr*egr sa*sa; generate n=50 method=detmax; run;Output 24.5.2: Optimal Design Using a Smaller Candidate Set

See "Handling Many Variables" for another example of reducing the candidate set for the optimal design search.
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