Nonlinear Programming by Avriel Mordecai;

Author:Avriel, Mordecai;
Language: eng
Format: epub
ISBN: 4901549
Publisher: Dover Publications
Published: 2012-10-03T16:00:00+00:00

(9.136)

for any two points x1 ≠ x2. It was also shown in Chapter 6 that a strongly quasiconvex function can attain its minimum on R″ (or over some convex subset of it) at no more than one point. In particular, this result holds for strictly pseudoconvex functions, for they are also strongly quasiconvex.

Theorem 9.6

Let f be a continuous strongly quasiconvex function on R″ that is to be minimized by the preceding method, starting with an arbitrary point . Suppose that the level set

(9.137)

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