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Finding Global Minima with a Computable Filled Function
Authors:Xian Liu
Affiliation:(1) Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada, T6G 2G7
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.
Keywords:Filled function method  Global optimization  Gradient Methods  Nonlinear programming
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