E04 Minimizing or Maximizing a Function

  • Published 1999

Abstract

The constraints involving A are called the general constraints. Note that upper and lower bounds are speci ed for all the variables and for all the general constraints. An equality constraint can be speci ed by setting li = ui. If certain bounds are not present, the associated elements of l or u can be set to special values that will be treated as 1 or +1. (See the description of the optional parameter inf bound in Section 8.2.) The de ning feature of a quadratic function f(x) is that the second-derivative matrix r2f(x) (the Hessian matrix) is constant. For the LP case, r2f(x) = 0; for QP1 and QP2, r2f(x) = H; and for QP3 and QP4, r2f(x) = HH. If H is de ned as the zero matrix, nag opt qp will solve the resulting linear programming problem; however, this can be accomplished more e ciently by setting the optional parameter prob = Nag LP, or by using nag opt lp (e04mfc).

Cite this paper

@inproceedings{1999E04MO, title={E04 Minimizing or Maximizing a Function}, author={}, year={1999} }