Fast Sequential Monte Carlo Methods For Counting And Optimization

Written by authorities in the field, this book presents an introduction to fast sequential Monte Carlo (SMC) methods for counting and optimization. Fast Sequential Monte Carlo Methods for Counting and Optimiztion is based on many years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, for counting problems, and for combinatorial optimization. Particular emphasis throughout the book is placed on cross-entropy, minimum cross-entropy, splitting, and stochastic enumeration. The overall aim is to make SMC methods accessible to readers who want to apply and to accentuate the unifying and novel mathematical ideas behind SMC in their future studies or work. Formal definitions (e.g. theorems and proofs) are embedded either in-text or in examples and experiments while case studies are emphasized when and where appropriate.

REUVEN Y. RUBINSTEIN, DSc, was Professor Emeritus in the Faculty of Industrial Engineering and Management at Technion-Israel Institute of Technology. The author of over 100 articles and six books, Dr. Rubinstein was also the inventor of the popular score-function method in simulation analysis and generic cross-entropy methods for combinatorial optimization and counting.

AD RIDDER, PhD, is Associate Professor of Operations Research at Vrije Universiteit Amsterdam. His research interests include rare event simulation, applied probability problems, queuing models, and Monte Carlo methods.

RADISLAV VAISMAN is the author of numerous journal articles, and his research interests include rare event simulation, randomized algorithms, and on-line planning.