A stochastic method for global optimization

C.G.E. Boender, A.H.G. Rinnooy Kan, G.T. Timmer, L. Stougie

    Research output: Contribution to JournalArticleAcademicpeer-review


    A stochastic method for global optimization is described and evaluated. The method involves a combination of sampling, clustering and local search, and terminates with a range of confidence intervals on the value of the global optimum. Computational results on standard test functions are included as well
    Original languageEnglish
    Pages (from-to)125-140
    JournalMathematical Programming
    Issue number1
    Publication statusPublished - 1982

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