Chapter Contents |
Previous |
Next |
The NLP Procedure |
The MINQUAD and MAXQUAD statements specify the H, g, and c, matrices that define a quadratic objective function. The MINQUAD statement is for minimizing the objective and the MAXQUAD statement is for maximizing the objective function.
The rows and columns in H and g correspond to the order of decision variables given in the DECVAR statement. Specifying the objective function with a MINQUAD or MAXQUAD statement indirectly defines the analytic derivatives for the objective function. Therefore, statements specifying derivatives are not valid in these cases. Also, only use these statements when TECH=LINCOMP or TECH=QUADAS and no nonlinear constraints are imposed.
There are three ways of using the MINQUAD or MAXQUAD statement:
proc nlp pall; array h[2,2] .4 0 0 4; minquad h, -100; decvar x1 x2 = -1; bounds 2 <= x1 <= 50, -50 <= x2 <= 50; lincon 10 <= 10 * x1 - x2; run;
proc nlp pall; minquad h, -100; decvar x1 x2; bounds 2 <= x1 <= 50, -50 <= x2 <= 50; lincon 10 <= 10 * x1 - x2; h1 = .4; h4 = 4; run;
proc nlp all; matrix h[1,1] = .4 4; minquad h, -100; decvar x1 x2 = -1; bounds 2 <= x1 <= 50; -50 <= x2 <= 50; lincon 10 <= 10 * x1 - x2; run;
Chapter Contents |
Previous |
Next |
Top |
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.