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by David G. Luenberger
Unifies the field of optimization with a few geometric principles The number of books that can legitimately be called classics in their fields is small indeed, but David Luenberger's OPtimization by Vector Space Methods certainly qualifies. Not only does Luenberger clearly demonstrate that a large segment of the field of optimization can be effectively unified by a few geometric principles of linear vector space theory, but his methods have found applications quite removed from the engineering problems to which they were first applied. Nearly 30 years after its initial publication, athis book is still among the most frequently cited sources in books and articles on financial optimization. The book uses functional analysis--the study of linear vector spaces--to impose problems. Thea early chapters offer an introduction to functional analysis, with applications to optimization. Topics addressed include linear space, Hilbert space, least-squares estimation, dual spaces, and linear operato
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