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The stochastics of threshold accepting: analysis of an application to the uniform design problem

In: Compstat 2006 - Proceedings in Computational Statistics

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  • Peter Winker

    (University of Giessen, Department of Economics)

Abstract

Threshold Accepting is a powerful optimization heuristic from the class of stochastic local search algorithms. It has been applied successfully to several problems in statistics and econometrics, including the uniform design problem. Using the latter application as an example, the stochastic properties of a TA implementation are analyzed. We provide a formal framework for the analysis of optimization heuristics, which can be used to estimate lower bounds and to derive convergence results. It is also helpful for tuning real applications. Empirical results are presented for the uniform design problem. In particular, the rate of convergence of the algorithm is estimated to be of the order of one over square root of the number of iterations.

Suggested Citation

  • Peter Winker, 2006. "The stochastics of threshold accepting: analysis of an application to the uniform design problem," Springer Books, in: Alfredo Rizzi & Maurizio Vichi (ed.), Compstat 2006 - Proceedings in Computational Statistics, pages 495-503, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-1709-6_40
    DOI: 10.1007/978-3-7908-1709-6_40
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