Finding global minima with a computable filled function. (English) Zbl 1033.90088

Liu, Xian

J. Glob. Optim. 19, No. 2, 151-161 (2001).

Summary: 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.

MSC:

90C26	Nonconvex programming, global optimization
90C30	Nonlinear programming

Keywords:

global optimization; gradient methods; filled function method; global minima of multidimensional nonconvex functions