This book presents the main methodological and theoretical developments in stochastic global optimization. The extensive text is divided into four chapters; the topics include the basic principles and methods of global random search, statistical inference in random search, Markovian and population-based random search methods, methods based on statistical models of multimodal functions and principles of rational decisions theory.
Key features: Inspires readers to explore various stochastic methods of global optimization by clearly explaining the main methodological principles and features of the methods; Includes a comprehensive study of probabilistic and statistical models underlying the stochastic optimization algorithms; Expands upon more sophisticated techniques including random and semi-random coverings, stratified sampling schemes, Markovian algorithms and population based algorithms; Provides a thorough description of the methods based on statistical models of objective function; Discusses criteria for evaluating efficiency of optimization algorithms and difficulties occurring in applied global optimization.
Stochastic learning and optimization is a multidisciplinary subject that has wide applications in modern engineering, social, and financial problems, including those in Internet and wireless communications, manufacturing, robotics, logistics, biomedical systems, and investment science. This book is unique in the following aspects.
A metaheuristic is a set of concepts that can be used to define heuristic methods that can be applied to a wide set of different problems. This volume presents a family of advanced methods of optimization called metaheuristics. This category covers simulated annealing, tabu search, evolutionary and genetic algorithms, and ant colonies. The book contains various case studies from engineering and operations research, and includes commented literature for each chapter.
Clearly organized, well-written, and user-friendly, <i>Educational Research</i>, provides a comprehensive look at quantitative, qualitative, and mixed-method approaches to research. Using concrete examples throughout, the book features a “Spotlight on Research” section, providing an extended look at three published articles per chapter. <p> The book has been created with a breadth and depth fitting a higher level course, yet is clear enough to accommodate students in advanced undergraduate classes. Set up in a modular format, this easy to read text can be followed in chronological order, or chapters can be used out of sequence to better serve your classroom needs. Rich in pedagogical features, <i>Educational Research</i> offers several elements that help the student to synthesize the main ideas of each chapter into the context of a real world researcher. <p>
In view of Professor Wendell Fleming's many fundamental contributions, his profound influence on the mathematical and systems theory communi- ties, his service to the profession, and his dedication to mathematics, we have invited a number of leading experts in the fields of control, optimiza- tion, and stochastic systems to contribute to this volume in his honor on the occasion of his 70th birthday. These papers focus on various aspects of stochastic analysis, control theory and optimization, and applications. They include authoritative expositions and surveys as well as research papers on recent and important issues. The papers are grouped according to the following four major themes: (1) large deviations, risk sensitive and Hoc control, (2) partial differential equations and viscosity solutions, (3) stochastic control, filtering and parameter esti- mation, and (4) mathematical finance and other applications. We express our deep gratitude to all of the authors for their invaluable contributions, and to the referees for their careful and timely reviews. We thank Harold Kushner for having graciously agreed to undertake the task of writing the foreword. Particular thanks go to H. Thomas Banks for his help, advice and suggestions during the entire preparation process, as well as for the generous support of the Center for Research in Scientific Computation. The assistance from the Birkhauser professional staff is also greatly appreciated.
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