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Global Optimization [electronic resource] :A Stochastic Approach / by Stefan Schäffler.

by Schäffler, Stefan [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Springer Series in Operations Research and Financial Engineering: Publisher: New York, NY : Springer New York : 2012.Description: XV, 147 p. 58 illus. online resource.ISBN: 9781461439271.Subject(s): Mathematics | Mathematical optimization | Mathematics | Optimization | Operations Research, Management ScienceDDC classification: 519.6 Online resources: Click here to access online
Contents:
Preface -- Introduction -- Preliminaries -- The Approach -- Theoretical Results -- The Algorithm -- Numerical Results -- References -- Index.
In: Springer eBooksSummary: This self-contained monograph presents a new stochastic approach to global optimization problems arising in a variety of disciplines including mathematics, operations research, engineering, and economics. The volume deals with constrained and unconstrained problems and puts a special emphasis on large scale problems. It also introduces a new unified concept for unconstrained, constrained, vector, and stochastic global optimization problems. All methods presented are illustrated by various examples. Practical numerical algorithms are given and analyzed in detail.   The topics presented include the randomized curve of steepest descent, the randomized curve of dominated points, the semi-implicit Euler method, the penalty approach, and active set strategies. The optimal decoding of block codes in digital communications is worked out as a case study and shows the potential and high practical relevance of this new approach.   Global Optimization: A Stochastic Approach is an elegant account of a refined theory, suitable for researchers and graduate students interested in global optimization and its applications.
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Preface -- Introduction -- Preliminaries -- The Approach -- Theoretical Results -- The Algorithm -- Numerical Results -- References -- Index.

This self-contained monograph presents a new stochastic approach to global optimization problems arising in a variety of disciplines including mathematics, operations research, engineering, and economics. The volume deals with constrained and unconstrained problems and puts a special emphasis on large scale problems. It also introduces a new unified concept for unconstrained, constrained, vector, and stochastic global optimization problems. All methods presented are illustrated by various examples. Practical numerical algorithms are given and analyzed in detail.   The topics presented include the randomized curve of steepest descent, the randomized curve of dominated points, the semi-implicit Euler method, the penalty approach, and active set strategies. The optimal decoding of block codes in digital communications is worked out as a case study and shows the potential and high practical relevance of this new approach.   Global Optimization: A Stochastic Approach is an elegant account of a refined theory, suitable for researchers and graduate students interested in global optimization and its applications.

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