Convergence Rate of the P-Algorithm for Optimization of Continuous Functions

  • James M. Calvin
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 42)


The P-algorithm is an adaptive algorithm for approximating the global minimum of a continuous function on an interval, motivated by viewing the function as a sample path of a Gaussian process. In this paper we analyze the convergence of the P-algorithm for arbitrary continuous functions, as well as under the assumption of Wiener measure on the objective functions. In both cases the convergence rate is described in terms of a parameter of the algorithm and a functional of the objective function.


Global optimization average complexity Brownian motion. 


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Copyright information

© Springer Science+Business Media Dordrecht 2000

Authors and Affiliations

  • James M. Calvin
    • 1
  1. 1.Department of Computer and Information ScienceNew Jersey Institute of TechnologyNewarkUSA

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