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Finding Global Minima with a Computable Filled Function

Journal of Global Optimization volume 19, pages 151–161 (2001)Cite this article

Abstract

The Filled Function Method is an approach to finding global minima of multidimensional nonconvex functions. The traditional filled functions have features that may affect the computability when applied to numerical optimization. This paper proposes a new filled function. This function needs only one parameter and does not include exponential terms. Also, the lower bound of weight factor a is usually smaller than that of one previous formulation. Therefore, the proposed new function has better computability than the traditional ones.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada, T6G 2G7

    Xian Liu

Authors
  1. Xian Liu
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Liu, X. Finding Global Minima with a Computable Filled Function. Journal of Global Optimization 19, 151–161 (2001). https://doi.org/10.1023/A:1008330632677

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  • DOI: https://doi.org/10.1023/A:1008330632677

  • Filled function method
  • Global optimization
  • Gradient Methods
  • Nonlinear programming