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Optimising Noisy Objective Functions

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Abstract

This discussion paper considers the use of stochastic algorithms for solving global optimisation problems in which function evaluations are subject to random noise. An idea is outlined for discussion at the forthcoming Stochastic Global Optimisation 2001 workshop in Hanmer in June; we propose that a noisy version of pure random search be studied.

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Reference

  1. Baumert, S. and Smith, R.L. (2001), Pure Random Search for Noisy Objective Functions, University of Michigan Technical Report 01-03

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Authors and Affiliations

  1. Statistics Department, Macquarie University, NSW, 2109, Australia

    David W. Bulger

  2. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, U.S.A

    H. Edwin Romeijn

Authors
  1. David W. Bulger
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  2. H. Edwin Romeijn
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Corresponding author

Correspondence to David W. Bulger.

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Bulger, D.W., Romeijn, H.E. Optimising Noisy Objective Functions. J Glob Optim 31, 599–600 (2005). https://doi.org/10.1007/s10898-004-9969-x

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  • DOI: https://doi.org/10.1007/s10898-004-9969-x

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