Stochastic Adaptive Search for Global Optimization

the long version

The book overviews several stochastic adaptive search methods for global optimization and provides analytical results regarding their performance and complexity. It develops a class of hit-and-run algorithms that are theoretically motivated and do not require fine-tuning of parameters. Several engineering global optimization problems are summarized to demonstrate the kinds of practical problems that are now within reach. Audience: This book is suitable for graduate students, researchers and practitioners in operations research, engineering, and mathematics.