A Triple Stabilized Bundle Method for Constrained Nonconvex Nonsmooth Optimization

被引:0
|
作者
Dembele, Andre [1 ]
Ndiaye, Babacar M. [2 ]
Ouorou, Adam [3 ]
Degla, Guy [1 ]
机构
[1] Univ Abomey Calavi, Inst Math & Phys Sci, Porto Novo, Benin
[2] Univ Cheikh Anta Diop Dakar, Lab Math Decis & Numer Anal, Dakar 45087, Senegal
[3] Orange Labs Res, Ave Republ, F-92320 Chatillon, France
关键词
Proximal algorithm; Bundle method; Nonconvex optimization; Nonsmooth optimization; Reformulation;
D O I
10.1007/978-3-030-38364-0_7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we provide an exact reformulation of Nonsmooth Constrained optimization Problems (NCP) using the Moreau-Yosida regularization. This reformulation allows the transformation of (NCP) to a sequence of convex programs of which solutions are feasible for (NCP). This sequence of solutions of auxiliary programs converges to a local solution of (NCP). Assuming Slater constraint qualification and basing on an exact penalization, our reformulation combined with a nonconvex proximal bundle method provides a local solution of (NCP). Our bundle method allows a strong update of the level set, may reduce significantly the number of null-steps and gives a new stopping criterion. Finally, numerical simulations are carried out.
引用
收藏
页码:75 / 87
页数:13
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