Matching stochastic algorithms to objective function landscapes

W. P. Baritompa*, M. Dür, E. M T Hendrix, L. Noakes, W. J. Pullan, G. R. Wood

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    7 Citations (Scopus)

    Abstract

    Large scale optimisation problems are frequently solved using stochastic methods. Such methods often generate points randomly in a search region in a neighbourhood of the current point, backtrack to get past barriers and employ a local optimiser. The aim of this paper is to explore how these algorithmic components should be used, given a particular objective function landscape. In a nutshell, we begin to provide rules for efficient travel, if we have some knowledge of the large or small scale geometry.

    Original languageEnglish
    Pages (from-to)579-598
    Number of pages20
    JournalJournal of Global Optimization
    Volume31
    Issue number4
    DOIs
    Publication statusPublished - Apr 2005

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