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

G. R. Wood*, Z. B. Zabinsky, B. P. Kristinsdottir

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    14 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)479-486
    Number of pages8
    JournalMathematical Programming, Series B
    Volume89
    Issue number3
    Publication statusPublished - Feb 2001

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