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by Radislav Vaisman, Ad Ridder, Reuven Y. Rubinstein
Fast Sequential Monte Carlo Methods for Counting and Optimization
Cover
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Copyright
Dedication
Chapter 1: Introduction to Monte Carlo Methods
Chapter 2: Cross-Entropy Method
2.1 Introduction
2.2 Estimation of Rare-Event Probabilities
2.3 Cross-Entropy Method forOptimization
2.4 Continuous Optimization
2.5 Noisy Optimization
Chapter 3: Minimum Cross-Entropy Method
3.1 Introduction
3.2 Classic MinxEnt Method
3.3 Rare Events and MinxEnt
3.4 Indicator MinxEnt Method
3.5 IME Method for Combinatorial Optimization
Chapter 4: Splitting Method for Counting and Optimization
4.1 Background
4.2 Quick Glance at the Splitting Method
4.3 Splitting Algorithm with Fixed Levels
4.4 Adaptive Splitting Algorithm
4.5 Sampling Uniformly on Discrete Regions
4.6 Splitting Algorithm for Combinatorial Optimization
4.7 Enhanced Splitting Method for Counting
4.8 Application of Splitting to Reliability Models
4.9 Numerical Results with the Splitting Algorithms
4.10 Appendix: Gibbs Sampler
Chapter 5: Stochastic Enumeration Method
5.1 Introduction
5.2 OSLA Method and Its Extensions
5.3 SE Method
5.4 Applications of SE
5.5 Numerical Results
Appendix A: Additional Topics
A.1 Combinatorial Problems
A.2 Information
A.3 Efficiency of Estimators
Bibliography
Abbreviations and Acronyms
List of Symbols
Index
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