Global Optimization

A Stochastic Approach

  • Stefan Schäffler

Table of contents

  1. Front Matter
    Pages i-xv
  2. Stefan Schäffler
    Pages 7-19
  3. Stefan Schäffler
    Pages 21-55
  4. Stefan Schäffler
    Pages 75-103
  5. Stefan Schäffler
    Pages 105-117
  6. Back Matter
    Pages 119-147

About this book

Introduction

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.

Keywords

Large scale optimization Predictor Corrector Method Probability Theory on Manifolds Randomized algorithms Unconstrained Global Optimization Vector Optimization

Authors and affiliations

  • Stefan Schäffler
    • 1
  1. 1., Fak. Elektro- und InformationstechnikUniversität der Bundeswehr MünchenNeubibergGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-3927-1
  • Copyright Information Springer Science+Business Media New York 2012
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-3926-4
  • Online ISBN 978-1-4614-3927-1
  • Series Print ISSN 1431-8598
  • About this book