Stochastic Optimization

  • Johannes Josef Schneider
  • Scott Kirkpatrick

Part of the Scientific Computation book series (SCIENTCOMP)

Table of contents

About this book

Introduction

The search for optimal solutions pervades our daily lives. From the scientific point of view, optimization procedures play an eminent role whenever exact solutions to a given problem are not at hand or a compromise has to be sought, e.g. to obtain a sufficiently accurate solution within a given amount of time. This book addresses stochastic optimization procedures in a broad manner, giving an overview of the most relevant optimization philosophies in the first part. The second part deals with benchmark problems in depth, by applying in sequence a selection of optimization procedures to them. While having primarily scientists and students from the physical and engineering sciences in mind, this book addresses the larger community of all those wishing to learn about stochastic optimization techniques and how to use them.

Keywords

Constraint Satisfaction Markov Monte Carlo Random Numbers Simulated Annealing Stochastic Optimization Tabu Search Traveling Salesman Problem algorithm algorithms construction genetic algorithms optimization

Authors and affiliations

  • Johannes Josef Schneider
    • 1
  • Scott Kirkpatrick
    • 2
  1. 1.Institut für Physik Fachbereich 08 Physik, Mathematik und InformatikJohannes Gutenberg-Universität MainzMainzGermany
  2. 2.The Selim and Rachel Benin School of Engineering and Computer ScienceThe Hebrew University of JerusalemJerusalemIsrael

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-34560-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-34559-6
  • Online ISBN 978-3-540-34560-2
  • Series Print ISSN 1434-8322
  • About this book