Mathematical Programming

, Volume 89, Issue 3, pp 479–486 | Cite as

Hesitant adaptive search: the distribution of the number of iterations to convergence

  • G.R. Wood
  • Z.B. Zabinsky
  • B.P. Kristinsdottir

Abstract.

Hesitant adaptive search is a stochastic optimisation procedure which accommodates hesitation, or pausing, at objective function values. It lies between pure adaptive search (which strictly improves at each iteration) and simulated annealing with constant temperature (which allows backtracking, or the acceptance of worse function values). In this paper we build on an earlier work and make two contributions; first, we link hesitant adaptive search to standard counting process theory, and second, we use this to derive the exact distribution of the number of iterations of hesitant adaptive search to termination.

Key words: global optimisation – adaptive search – simulated annealing – point process – convergence rate 
Mathematics Subject Classification (1991): 90C65, 90C30, 65K05 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • G.R. Wood
    • 1
  • Z.B. Zabinsky
    • 2
  • B.P. Kristinsdottir
    • 2
  1. 1.Institute of Information Sciences and Technology, Massey University, Palmerston North, New ZealandNZ
  2. 2.Industrial Engineering Program, University of Washington, Seattle, WA 98195-2650, USAUS

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