5 papers
A Multiscale Primal-Dual Interior-Point Relaxation Method for Large-Scale Optimal Transport Problems
Shengyu Sun, Rui-Jin Zhang, Ruoyu Diao +1
Large-scale optimal transport (OT) problems involve a vast number of transport variables, leading to prohibitive memory and computational costs. To address these challenges, we pro…
A primal--dual interior-point method for nonsymmetric conic optimization with conjugate-free scaling
Rui-Jin Zhang, Wenhao Fu, Yu-Hong Dai
We develop a primal--dual interior-point method for nonsymmetric conic optimization based on a conjugate-free scaling matrix. The scaling is obtained from a single-secant BFGS upda…
Polynomial iteration complexity of a path-following smoothing Newton method for symmetric cone programming
Yu-Hong Dai, Ruoyu Diao, Xin-Wei Liu +1
It has long remained open whether smoothing Newton methods (SNMs) for symmetric cone programming (SCP) admit polynomial iteration complexity. A key difficulty lies in the lack of a…
A Newton Augmented Lagrangian Method for Symmetric Cone Programming with Complexity Analysis
Rui-Jin Zhang, Ruoyu Diao, Xin-Wei Liu +1
Symmetric cone programming covers a broad class of convex optimization problems, including linear programming, second-order cone programming, and semidefinite programming. Although…
An Efficient Benders Decomposition Approach for Optimal Large-Scale Network Slicing
Wei-Kun Chen, Zheyu Wu, Rui-Jin Zhang +3
This paper considers the network slicing (NS) problem which attempts to map multiple customized virtual network requests to a common shared network infrastructure and allocate netw…