An active-set with barrier method and trust-region mechanism to solve a nonlinear Bilevel programming problem

被引:2
|
作者
El-Sobky, B. [1 ]
Ashry, G. [1 ]
Abo-Elnaga, Y. [2 ]
机构
[1] Alexandria Univ, Fac Sci, Dept Math & Comp Sci, Alexandria, Egypt
[2] Higher Technol Inst, Dept basic Sci, Tenth Of Ramadan City, Egypt
来源
AIMS MATHEMATICS | 2022年 / 7卷 / 09期
关键词
nonlinear Bilevel programming problem; active-set; barrier method; trust-region mechanism; projected Hessian mechanism; global convergence; DESCENT METHOD; NCP-FUNCTIONS; ALGORITHM; OPTIMIZATION;
D O I
10.3934/math.2022882
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Nonlinear Bilevel programming (NBLP) problem is a hard problem and very difficult to be resolved by using the classical method. In this paper, Karush-Kuhn-Tucker (KKT) condition is used with Fischer-Burmeister function to convert NBLP problem to an equivalent smooth single objective nonlinear programming (SONP) problem. An active-set strategy is used with Barrier method and trust region technique to solve the smooth SONP problem effectively and guarantee a convergence to optimal solution from any starting point. A global convergence theory for the active-set barrier trust-region (ACBTR) algorithm is studied under five standard assumptions. An applications to mathematical programs are introduced to clarify the effectiveness of ACBTR algorithm. The results show that ACBTR algorithm is stable and capable of generating approximal optimal solution to the NBLP problem.
引用
收藏
页码:16112 / 16146
页数:35
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