Facts, conjectures, and improvements for simulated annealing /

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Bibliographic Details
Author / Creator:Salamon, Peter, 1950-
Imprint:Philadelphia : Society for Industrial and Applied Mathematics, c2002.
Description:xiii, 150 p. : ill. ; 26 cm.
Language:English
Series:SIAM monographs on mathematical modeling and computation
Subject:
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/4818610
Hidden Bibliographic Details
Other authors / contributors:Sibani, Paolo, 1954-
Frost, Richard, 1955-
ISBN:0898715083 (pbk.)
Notes:Includes bibliographical references (p. 129-137) and index.
Table of Contents:
  • List of Figures
  • Preface
  • Acknowledgments
  • I. Overview
  • 1. The Place of Simulated Annealing in the Arsenal of Global Optimization
  • 2. Six Simulated Annealing Problems
  • 2.1. Problem Definitions
  • 2.2. Move Classes
  • 3. Nomenclature
  • 4. Bare-Bones Simulated Annealing
  • II. Facts
  • 5. Equilibrium Statistical Mechanics
  • 5.1. The Number of States That Realize a Distribution
  • 5.2. Derivation of the Boltzmann Distribution
  • 5.3. Averages and Fluctuations
  • 6. Relaxation Dynamics--Finite Markov Chains
  • 6.1. Finite Markov Chains
  • 6.2. Reversibility and Stationary Distributions
  • 6.3. Relaxation to the Stationary Distribution
  • 6.4. Equilibrium Fluctuations
  • 6.4.1. The Correlation Function
  • 6.4.2. Linear Response and the Decay of the Correlation Function
  • 6.5. Standard Examples of the Relaxation Paradigm
  • 6.5.1. Two-State System
  • 6.5.2. A Folk Theorem--Arrhenius' or Kramers' Law
  • 6.6. Glassy Systems
  • III. Improvements and Conjectures
  • 7. Ensembles
  • 8. The Brick Wall Effect and Optimal Ensemble Size
  • 9. The Objective Function
  • 9.1. Imperfectly Known Objective
  • 9.2. Implications of Noise
  • 9.3. Deforming the Energy
  • 9.4. Eventually Monotonic Deformations
  • 10. Move Classes and Their Implementations
  • 10.1. What Makes a Move Class Good?
  • 10.1.1. Natural Scales
  • 10.1.2. Correlation Length and Correlation Time
  • 10.1.3. Relaxation Time at Finite T
  • 10.1.4. Combinatorial Work
  • 10.2. More Refined Move Schemes
  • 10.2.1. Basin Hopping
  • 10.2.2. Fast Annealing
  • 10.2.3. Rejectionless Monte Carlo
  • 11. Acceptance Rules
  • 11.1. Tsallis Acceptance Probabilities
  • 11.2. Threshold Accepting
  • 11.3. Optimality of Threshold Accepting
  • 12. Thermodynamic Portraits
  • 12.1. Equilibrium Information
  • 12.1.1. Histogram Method
  • 12.2. Dynamic Information
  • 12.2.1. Transition Matrix Method
  • 12.3. Time-Resolved Information
  • 12.A. Appendix: Why Lumping Preserves the Stationary Distribution
  • 13. Selecting the Schedule
  • 13.1. Start and Stop Temperatures
  • 13.2. Simple Schedules
  • 13.2.1. The Sure-to-Get-You-There Schedule
  • 13.2.2. The Exponential Schedule
  • 13.2.3. Other Simple Schedules
  • 13.3. Adaptive Cooling
  • 13.3.1. Using the System's Scale of Time
  • 13.3.2. Using the System's Scale of Energy
  • 13.3.3. Using Both Energy and Time Scales
  • 13.4. Nonmonotonic Schedules
  • 13.5. Conclusions Regarding Schedules
  • 14. Estimating the Global Minimum Energy
  • IV. Toward Structure Theory and Real Understanding
  • 15. Structure Theory of Complex Systems
  • 15.1. The Coarse Structure of the Landscape
  • 15.2. Exploring the State Space Structure: Tools and Concepts
  • 15.3. The Structure of a Basin
  • 15.4. Examples
  • 15.A. Appendix: Entropic Barriers
  • 15.A.1. The Master Equation
  • 15.A.2. Random Walks on Flat Landscapes
  • 15.A.3. Bounds on Relaxation Times for General Graphs
  • 16. What Makes Annealing Tick?
  • 16.1. The Dynamics of Draining a Basin
  • 16.2. Putting It Together
  • 16.3. Conclusions
  • V. Resources
  • 17. Supplementary Materials
  • 17.1. Software
  • 17.1.1. Simulated Annealing from the Web
  • 17.1.2. The Methods of This Book
  • 17.1.3. Software Libraries
  • 17.2. Energy Landscapes Database
  • Bibliography
  • Index