Mathematical Programming

, Volume 22, Issue 1, pp 125–140

A stochastic method for global optimization

  • C. G. E. Boender
  • A. H. G. Rinnooy Kan
  • G. T. Timmer
  • L. Stougie
Article

Abstract

A stochastic method for global optimization is described and evaluated. The method involves a combination of sampling, clustering and local search, and terminates with a range of confidence intervals on the value of the global optimum. Computational results on standard test functions are included as well.

Key words

Stochastic Methods Global Optimization Clustering Confidence Interval 

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Copyright information

© The Mathematical Programming Society, Inc. 1982

Authors and Affiliations

  • C. G. E. Boender
    • 1
  • A. H. G. Rinnooy Kan
    • 1
  • G. T. Timmer
    • 1
  • L. Stougie
    • 2
  1. 1.Econometric InstituteErasmus UniversityRotterdamThe Netherlands
  2. 2.Mathematical CentreAmsterdamThe Netherlands

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