Annals of Operations Research

, Volume 1, Issue 2, pp 111–128 | Cite as

A Bayesian algorithm for global optimization

  • B. Betrò
  • R. Rotondi
Global Optimization


A crucial step in global optimization algorithms based on random sampling in the search domain is decision about the achievement of a prescribed accuracy. In order to overcome the difficulties related to such a decision, the Bayesian Nonparametric Approach has been introduced. The aim of this paper is to show the effectiveness of the approach when an ad hoc clustering technique is used for obtaining promising starting points for a local search algorithm. Several test problems are considered.

Keywords and phrases

Global optimization Bayesian nonparametric inference random distributions cluster analysis 


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Copyright information

© J.C. Baltzer A.G., Scientific Publishing Company 1984

Authors and Affiliations

  • B. Betrò
    • 1
  • R. Rotondi
    • 1
  1. 1.CNR-IAMIMilanoItaly

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