Journal of the Operations Research Society of China

所属专题: Continuous Optimization

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  • 出版日期:2017-06-30 发布日期:2017-06-30

Optimization Methods for Box-Constrained Nonlinear Programming Problems Based on Linear Transformation and Lagrange Interpolating Polynomials

  • Online:2017-06-30 Published:2017-06-30

Abstract:

In this paper, an optimality condition for nonlinear programming problems
with box constraints is given by using linear transformation and Lagrange interpolating
polynomials. Based on this condition, two new local optimization methods are
developed. The solution points obtained by the new local optimization methods can
improve the Karush–Kuhn–Tucker (KKT) points in general. Two global optimization
methods then are proposed by combining the two new local optimization methods
with a filled function method. Some numerical examples are reported to show the
effectiveness of the proposed methods.

Key words: Nonlinear programming ·, Optimality conditions ·, Linear transformation ·
Lagrange interpolating polynomials ·,
Global optimization method