Proximity control in bundle methods for convex
Mathematical Programming: Series A and B
A quasi-second-order proximal bundle algorithm.
Mathematical Programming: Series A and B
A bundle-Newton method for nonsmooth unconstrained minimization
Mathematical Programming: Series A and B
Globally convergent variable metric method for convex nonsmooth unconstrained minimization
Journal of Optimization Theory and Applications
Algorithm 811: NDA: algorithms for nondifferentiable optimization
ACM Transactions on Mathematical Software (TOMS)
SIAM Journal on Optimization
A method of truncated codifferential with application to some problems of cluster analysis
Journal of Global Optimization
Minimizing Nonconvex Nonsmooth Functions via Cutting Planes and Proximity Control
SIAM Journal on Optimization
Globally convergent limited memory bundle method for large-scale nonsmooth optimization
Mathematical Programming: Series A and B
An algorithm for the estimation of a regression function by continuous piecewise linear functions
Computational Optimization and Applications
A Redistributed Proximal Bundle Method for Nonconvex Optimization
SIAM Journal on Optimization
Codifferential method for minimizing nonsmooth DC functions
Journal of Global Optimization
| Hi-index | 7.29 |
A new algorithm is developed based on the concept of codifferential for minimizing the difference of convex nonsmooth functions. Since the computation of the whole codifferential is not always possible, we use a fixed number of elements from the codifferential to compute the search directions. The convergence of the proposed algorithm is proved. The efficiency of the algorithm is demonstrated by comparing it with the subgradient, the truncated codifferential and the proximal bundle methods using nonsmooth optimization test problems.