## Simulated Annealing: Parallelization TechniquesThis edited collection of papers, the result of an 18-month workshop held at France's Ecole Normale Superierure, covers the most current research on implementing the simulated algorithm on parallel computers. Professionals and students in mathematics, computer science, and electrical engineering will find theoretical results as well as actual simulations on existing parallel computers, sketching applications in discrete math, chip placement problems and spin glass models. |

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### Contents

A Common Large Deviations Mathematical | 11 |

Parallel Annealing by Periodically Interacting | 47 |

Parallel Annealing by Periodically Interacting | 81 |

Copyright | |

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### Common terms and phrases

Aarts acceptance rate accepted moves annealing schemes architecture Assume asymptotic configuration attraction domain average behavior Catoni Chapter communication computation configuration space constant cooling schedule Tn cycle decreasing defined denote distribution elementary moves energy function energy landscape evaluate example experimental exponential Figure finite fixed Freidlin Geman given global minimum graph Hence Henri Poincare high temperature hypercube implementation initial configuration Kirkpatrick logarithmic low temperature mode Markov chain matrix mesh method Metropolis algorithm MIMD neighborhood neighbors number of iterations number of processors objective function observed probability obtained parallel algorithm parallel annealing parallel computer parallel simulated annealing parameter periodically interacting perturbations placement problem plateau probability measure random rate of convergence Section sequence sequential algorithm sequential annealing SIMD simulated annealing algorithm solution speed of convergence spin glass SPMD synchronization temperature step tetrahedrons Theorem tion topology transition transputers updating