A modified standard embedding with jumps in nonlinear optimization

doi:10.1016/j.ejor.2004.08.048

A modified standard embedding with jumps in nonlinear optimization

2006-03-01

6

OA

AI

DOI：10.1016/j.ejor.2004.08.048

原文链接

查看原文

摘要

En 中文

The paper deals with a combination of pathfollowing methods (embedding approach) and feasible descent direction methods (so-called jumps) for solving a nonlinear optimization problem with equality and inequality constraints. Since the method that we propose here uses jumps from one connected component to another one, more than one connected component of the solution set of the corresponding one-parametric problem can be followed numerically. It is assumed that the problem under consideration belongs to a generic subset which was introduced by Jongen, Jonker and Twilt. There already exist methods of this type for which each starting point of a jump has to be an endpoint of a branch of local minimizers. In this paper the authors propose a new method by allowing a larger set of starting points for the jumps which can be constructed at bifurcation and turning points of the solution set. The topological properties of those cases where the method is not successful are analyzed and the role of constraint qualifications in this context is discussed. Furthermore, this new method is applied to a so-called modified standard embedding which is a particular construction without equality constraints. Finally, an algorithmic version of this new method as well as computational results are presented. (c) 2005 Published by Elsevier B.V.

Keyword:

parametric programming

pathfollowing methods with jumps

genericity

Jongen-Jonker-Twilt regularity

modified standard embedding

A modified standard embedding with jumps in nonlinear optimization

摘要

AI总结

期刊

机构

引用论文