Backtracking adaptive search: Distribution of number of iterations to convergence

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

doi:10.1007/s10957-006-9040-9

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 journal › Article › peer-review

3 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 language	English
Pages (from-to)	547-562
Number of pages	16
Journal	Journal of Optimization Theory and Applications
Volume	128
Issue number	3
DOIs	https://doi.org/10.1007/s10957-006-9040-9
Publication status	Published - Mar 2006

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title = "Backtracking adaptive search: Distribution of number of iterations to convergence",

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.",

author = "Wood, {G. R.} and Bulger, {D. W.} and Baritompa, {W. P.} and Alexander, {D. L J}",

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AU - Wood, G. R.

AU - Bulger, D. W.

AU - Baritompa, W. P.

AU - Alexander, D. L J

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AB - 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.

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JO - Journal of Optimization Theory and Applications

JF - Journal of Optimization Theory and Applications

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ER -

Backtracking adaptive search: Distribution of number of iterations to convergence

Abstract

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