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099 eBook O’Reilly for Public Libraries
100 1 Rubinstein, Reuven Y.
245 10 Fast sequential Monte Carlo methods for counting and
optimization /|cReuven Rubinstein, Faculty of Industrial
Engineering and Management, Technion, Israel Institute of
Technology, Haifa, Israel, Ad Ridder, Department of
Econometrics and Operations Research, Vrije University,
Amsterdam, Netherlands, Radislav Vaisman, Faculty of
Industrial Engineering and Management, Technion, Israel
Institute of Technology, Haifa, Israel.|h[O'Reilly
electronic resource]
264 1 Hoboken, New Jersey :|bJohn Wiley & Sons, Inc.,|c[2013]
300 1 online resource
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
504 Includes bibliographical references and index.
505 0 Series; 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.
505 8 4.3 Splitting Algorithm with Fixed Levels4.4 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.
505 8 A.3 Efficiency of EstimatorsBibliography; Abbreviations
and Acronyms; List of Symbols; Index; Series.
520 This book presents the first comprehensive account of fast
sequential Monte Carlo (SMC) methods for counting and
optimization at an exceptionally accessible level. Written
by authorities in the field, it places great emphasis 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.
588 0 Print version record and CIP data provided by publisher.
590 O'Reilly|bO'Reilly Online Learning: Academic/Public
Library Edition
650 0 Monte Carlo method.
650 0 Mathematical optimization.
650 2 Monte Carlo Method
650 6 Méthode de Monte-Carlo.
650 6 Optimisation mathématique.
650 7 Mathematical optimization|2fast
650 7 Monte Carlo method|2fast
650 7 Sequenzielle Monte-Carlo-Methode|2gnd
650 7 Optimierung|2gnd
700 1 Ridder, Ad,|d1955-
700 1 Vaisman, Radislav.
776 08 |iPrint version:|aRubinstein, Reuven Y.|tFast sequential
Monte Carlo methods for counting and optimization.
|dHoboken, New Jersey : John Wiley & Sons, Inc., [2013]
|z9781118612262|w(DLC) 2013011113
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
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