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Monte Carlo Optimization

Chapter
Part of the Use R book series (USE R)

Abstract

This chapter is the equivalent for optimization problems of what Chapter 3 is for integration problems. We distinguish between two separate uses of computer-generated random variables to solve optimization problems. The first use, as seen in Section 5.3, is to produce stochastic search techniques to reach the maximum (or minimum) of a function, devising random exploration techniques on the surface of this function that avoid being trapped in local maxima (or minima) and are sufficiently attracted by the global maximum (or minimum). The second use, described in Section 5.4, is closer to Chapter 3 in that simulation is used to approximate the function to be optimized.

Keywords

Importance Sampling Stochastic Approximation Stochastic Search Monte Carlo Experiment Monte Carlo Approximation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Université Paris Dauphine UMR CNRS 7534 CEREMADEParis cedex 16France
  2. 2.Department of StatisticsUniversity of FloridaGainesvilleUSA

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