Backtracking adaptive search: Distribution of number of iterations to convergence

G. R. Wood*, D. W. Bulger, W. P. Baritompa, D. L J Alexander

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)

    Abstract

    Backtracking adaptive search is a simplified stochastic optimiza-tion procedure which permits the acceptance of worsening objective function values. It generalizes the hesitant adaptive search, which in turn is a gener-alization of the pure adaptive search. In this paper, we use ideas from the theory of stochastic processes to determine the full distribution of the number of iterations to convergence for the backtracking adaptive search.

    Original languageEnglish
    Pages (from-to)547-562
    Number of pages16
    JournalJournal of Optimization Theory and Applications
    Volume128
    Issue number3
    DOIs
    Publication statusPublished - Mar 2006

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