Abstract Convexity and Global Optimization
By: by Alexander Rubinov
Series: Nonconvex Optimization and Its Applications -- 44; Nonconvex optimization and its applications -- 44.
Publisher: Springer US
Published: 2000
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] /
Number of pages: 493
ISBN-13: 9781441948311; 9781475732009
Subjects: Mathematics; Mathematical optimization; Computer engineering
Description: This book consists of two parts. Firstly, the main notions of abstract convexity and their applications in the study of some classes of functions and sets are presented. Secondly, both theoretical and numerical aspects of global optimization based on abstract convexity are examined. Most of the book does not require knowledge of advanced mathematics. Classical methods of nonconvex mathematical programming, being based on a local approximation, cannot be used to examine and solve many problems of global optimization, and so there is a clear need to develop special global tools for solving these problems. Some of these tools are based on abstract convexity, that is, on the representation of a function of a rather complicated nature as the upper envelope of a set of fairly simple functions. Audience: The book will be of interest to specialists in global optimization, mathematical programming, and convex analysis, as well as engineers using mathematical tools and optimization techniques and specialists in mathematical modelling.
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