Newton's method may fail to recognize proximity to optimal points in constrained optimization

• 成果类型: Article
• 署名作者: Andreani, R.; Martinez, J. M.; Santos, L. T.
• 署名单位: Universidade Estadual de Campinas
• 刊物名称: MATHEMATICAL PROGRAMMING
• ISSN/ISSBN: 0025-5610
• DOI: 10.1007/s10107-016-0994-6
• 发表日期: 2016
• 页码: 547-555
• 关键词: sqp

摘要

We will show examples in which the primal sequence generated by the Newton-Lagrange method converges to a strict local minimizer of a constrained optimization problem but the gradient of the Lagrangian does not tend to zero, independently of the choice of the dual sequence.