Theory of Global Random Search
 364 Pages
 March 31, 1991
 0.85 MB
 4178 Downloads
 English
Springer
Applied mathematics, Computer Programming, Search theory, Mathematics, Science/Mathematics, Stochastic Processes, Linear Programming, Operations Research, Probability & Statistics  General, Business & EconomicsOperations Research, Mathematics / Linear Programming, Mathematics / Statistics, MathematicsLinear Programming, Mathematical optimiz
Contributions  János D. Pintér (Editor) 
The Physical Object  

Format  Hardcover 
ID Numbers  
Open Library  OL7806535M 
ISBN 10  0792311221 
ISBN 13  9780792311225 
Theory of Global Random Search. Authors: Zhigljavsky, Anatoly A. Editors: Pintér, János D. (Ed.) Free Preview. Global Optimization Theory: General Concepts  2. Global Optimization Methods  2. Global Random Search  3.
Main Concepts and Approaches of Global Random Search  4. Statistical Inference in Global Random Search  5. Methods of Generations  6. Random Search Algorithms for Solving Specific Problems  3.
Auxiliary Results  7. Theory of Global Random Search. Authors (view affiliations) Anatoly A. Zhigljavsky; Editors; J.
Details Theory of Global Random Search FB2
Pintér Search within book. Front Matter. Pages ixviii. PDF. Global Optimization: An Overview Theory of Global Random Search book A. Zhigljavsky, J. Pintér. Pages Global Random Search. Main Concepts and Approaches of Global Random Search. Anatoly A. Zhigljavsky.
Download Theory of Global Random Search FB2
Theory of Global Random Search (Mathematics and its Applications) st Edition by Anatoly A. Zhigljavsky (Author), János D. Pintér (Editor) ISBN ISBN Why is ISBN important. ISBN. This barcode number lets you verify that you're getting exactly the right version or edition of a book.
Cited by: Search the world's most comprehensive index of fulltext books. My library. Global optimization is a branch of applied mathematics and numerical analysis that attempts to find the global minima or maxima of a function or a set of functions on a given set. It is usually described as a minimization problem because the maximization of the realvalued function () is obviously equivalent to the minimization of the function ():= (−) ⋅ ().
Zhigljavsky A.A., Pintér J. () Random Search Algorithms for Solving Specific Problems. In: Pintér J. (eds) Theory of Global Random Search.
Mathematics and Its Author: Anatoly A.
Description Theory of Global Random Search EPUB
Zhigljavsky, J. Pintér. DOWNLOAD FREE Ebooks Theory of Global Random Search (Mathematics and its Applications) Full. The objective of Risk Analysis in Theory and Practice is to present this analytical framework and to illustrate how it can be used in the investigation of economic decisions under risk.
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the author provides a vast bibliography on the subject. Stochastic optimization (SO) methods are optimization methods that generate and use random stochastic problems, the random variables appear in the formulation of the optimization problem itself, which involves random objective functions or random constraints.
Stochastic optimization methods also include methods with random iterates. Random search belongs to the fields of Stochastic Optimization and Global Optimization.
Random search is a direct search method as it does not require derivatives to search a continuous domain. This base approach is related to techniques that provide small improvements such as Directed Random Search, and Adaptive Random Search.
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In theory, that's a fairly simple system, almost a Newtonian system. A new variant of pure random search (PRS) for function optimization is introduced. The basic finitedescent accelerated random search (ARS) algorithm is simple: the search is confined to shrinking neighborhoods of a previous recordgenerating value, with the search neighborhood reinitialized to the entire space when a new record is found.
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