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＜電子ブック＞
Introduction to Global Optimization Exploiting Space-Filling Curves / by Yaroslav D. Sergeyev, Roman G. Strongin, Daniela Lera
(SpringerBriefs in Optimization. ISSN:2191575X)

版	1st ed. 2013.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2013
本文言語	英語
大きさ	X, 125 p. 32 illus., 30 illus. in color : online resource
著者標目	*Sergeyev, Yaroslav D author Strongin, Roman G author Lera, Daniela author SpringerLink (Online service)
件　名	LCSH:Manifolds (Mathematics) LCSH:Operations research LCSH:Management science LCSH:Computer software LCSH:Numerical analysis LCSH:Algebraic geometry FREE:Manifolds and Cell Complexes FREE:Operations Research, Management Science FREE:Mathematical Software FREE:Numerical Analysis FREE:Algebraic Geometry
一般注記	1. Introduction -- 2. Approximations to Peano curves -- 3. Global optimization algorithms using curves to reduce dimensionality of the problem -- 4. Ideas for acceleration -- 5. A brief conclusion -- References Introduction to Global Optimization Exploiting Space-Filling Curves provides an overview of classical and new results pertaining to the usage of space-filling curves in global optimization. The authors look at a family of derivative-free numerical algorithms applying space-filling curves to reduce the dimensionality of the global optimization problem; along with a number of unconventional ideas, such as adaptive strategies for estimating Lipschitz constant, balancing global and local information to accelerate the search. Convergence conditions of the described algorithms are studied in depth and theoretical considerations are illustrated through numerical examples. This work also contains a code for implementing space-filling curves that can be used for constructing new global optimization algorithms. Basic ideas from this text can be applied to a number of problems including problems with multiextremal and partially defined constraints and non-redundant parallel computations can be organized. Professors, students, researchers, engineers, and other professionals in the fields of pure mathematics, nonlinear sciences studying fractals, operations research, management science, industrial and applied mathematics, computer science, engineering, economics, and the environmental sciences will find this title useful . HTTP:URL=https://doi.org/10.1007/978-1-4614-8042-6

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