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Nondifferentiable and Two-Level Mathematical Programming (Paperback, Softcover reprint of the original 1st ed. 1997)
Loot Price: R4,284
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Nondifferentiable and Two-Level Mathematical Programming (Paperback, Softcover reprint of the original 1st ed. 1997)
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The analysis and design of engineering and industrial systems has
come to rely heavily on the use of optimization techniques. The
theory developed over the last 40 years, coupled with an increasing
number of powerful computational procedures, has made it possible
to routinely solve problems arising in such diverse fields as
aircraft design, material flow, curve fitting, capital expansion,
and oil refining just to name a few. Mathematical programming plays
a central role in each of these areas and can be considered the
primary tool for systems optimization. Limits have been placed on
the types of problems that can be solved, though, by the difficulty
of handling functions that are not everywhere differentiable. To
deal with real applications, it is often necessary to be able to
optimize functions that while continuous are not differentiable in
the classical sense. As the title of the book indicates, our chief
concern is with (i) nondifferentiable mathematical programs, and
(ii) two-level optimization problems. In the first half of the
book, we study basic theory for general smooth and nonsmooth
functions of many variables. After providing some background, we
extend traditional (differentiable) nonlinear programming to the
nondifferentiable case. The term used for the resultant problem is
nondifferentiable mathematical programming. The major focus is on
the derivation of optimality conditions for general
nondifferentiable nonlinear programs. We introduce the concept of
the generalized gradient and derive Kuhn-Tucker-type optimality
conditions for the corresponding formulations.
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