This book presents the main methodological and theoretical developments in stochastic global optimization. The extensive text is divided into four chapters; some of the topics include an introduction to global random search, statistical inference, several associated random search algorithms, and various approaches to statistical models.
This book examines the main methodological and theoretical developments in stochastic global optimization. It is designed to inspire readers to explore various stochastic methods of global optimization by clearly explaining the main methodological principles and features of the methods. Among the book's features is a comprehensive study of probabilistic and statistical models underlying the stochastic optimization algorithms.
Basic Concepts and Ideas.- Global Random Search: Fundamentals and Statistical Inference.- Global Random Search: Extensions.- Methods Based on Statistical Models of Multimodal Functions.
From the reviews:
"This excellent book is written for researchers interested in global optimization. ... the approach of carrying through from basic ideas to the most recent techniques will make this a valuable resource for the initiated. ... Gathering together contemporary methods and developments in stochastic global optimization, this text presents four chapters." (Tom Schulte, MathDL, February, 2008)
"For global optimization, based on former monographs and articles of the authors on (global) random search, in this book global random search methods and stochastic models for the objective function are presented. ... This well-written book contains many references on the field of (global) random search techniques." (Kurt Marti, Mathematical Reviews, Issue 2008 j)
"The aim of the book is to present the major methodological and theoretical developments in the field of stochastic global optimization including global random search and methods based on probabilistic assumptions about the objective function. The book contains four chapters. ... The book also contains an index. The book is well written and the presentation is ... self-contained." (I. M. Stancu-Minasian, Zentralblatt MATH, Vol. 1136 (14), 2008)
Preface.- Introduction.- Basic Concepts and Ideas.- Global Random Search: Fundamentals and Statistical Inference.- Global Random Search: Extensions.- Statistical Models.- References.- Index.
Provides reader with a methodological and theoretical basis for developing and investigating optimization heuristics
Summarizes basic ideas and presents recent progress and new results
Includes an extensive bibliography with old Russian articles as well as new English papers
Includes an extensive discussion on probabilistic and statistical models used in the global random search
Expands upon more sophisticated techniques including random and semi-random coverings, stratified sampling schemes, Markovian algorithms and populations based algorithms