A multi-step doubly stabilized bundle method for nonsmooth convex optimization
作者：
Highlights：
• We propose a multi-step doubly stabilized bundle method for solving nonsmooth convex optimization problems.
• Three related iteration sequences are generated instead of a single sequence used before.
• A new descent test criterion is proposed, aiming to take advantage of the multi-step scheme.
• Global convergence of the algorithm is established.
• Numerical results are very encouraging.
摘要
•We propose a multi-step doubly stabilized bundle method for solving nonsmooth convex optimization problems.•Three related iteration sequences are generated instead of a single sequence used before.•A new descent test criterion is proposed, aiming to take advantage of the multi-step scheme.•Global convergence of the algorithm is established.•Numerical results are very encouraging.
论文关键词：Nonsmooth optimization,Doubly stabilized bundle method,Multi-step scheme,Descent test criterion,Global convergence
论文评审过程：Received 12 July 2019, Revised 2 January 2020, Accepted 9 February 2020, Available online 27 February 2020, Version of Record 27 February 2020.
论文官网地址：https://doi.org/10.1016/j.amc.2020.125154
