Abstract
Fully describes optimization methods that are currently most valuable in
solving real-life problems. Since optimization has applications in almost
every branch of science and technology, the text emphasizes their practical
aspects in conjunction with the heuristics useful in making them perform more
reliably and efficiently. To this end, it presents comparative numerical
studies to give readers a feel for possibile applications and to illustrate
the problems in assessing evidence. Also provides theoretical background which
provides insights into how methods are derived. This edition offers revised
coverage of basic theory and standard techniques, with updated discussions of
line search methods, Newton and quasi-Newton methods, and conjugate direction
methods, as well as a comprehensive treatment of restricted step or trust
region methods not commonly found in the literature. Also includes recent
developments in hybrid methods for nonlinear least squares; an extended
discussion of linear programming, with new methods for stable updating of LU
factors; and a completely new section on network programming. Chapters include
computer subroutines, worked examples, and study questions.
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