14 citations · 30 across the 8 of their papers we have counts for
8 papers
Automating Reformulation for Parallel ADMM
Kaizhao Sun, Baihao Wu, Kun Yuan +1
Many real-world optimization models contain exploitable sparsity and block structure, but this structure is often obscured in algebraic form, limiting the effectiveness of modern p…
ALiA: Adaptive Linearized ADMM
Uijeong Jang, Kaizhao Sun, Wotao Yin +1
We propose ALiA, a novel adaptive variant of the alternating direction method of multipliers (ADMM). Specifically, ALiA is a variant of function-linearized proximal ADMM (FLiP ADMM…
Smoothed Proximal Lagrangian Method for Nonlinear Constrained Programs
Wenqiang Pu, Kaizhao Sun, Jiawei Zhang
This paper introduces a smoothed proximal Lagrangian method for minimizing a nonconvex smooth function over a convex domain with additional explicit convex nonlinear constraints. T…
Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition
Ignacio Aravena, Daniel K. Molzahn, Shixuan Zhang +12
The optimal power flow problem is central to many tasks in the design and operation of electric power grids. This problem seeks the minimum cost operating point for an electric pow…
An ADMM-based Distributed Optimization Method for Solving Security-Constrained AC Optimal Power Flow
Amin Gholami, Kaizhao Sun, Shixuan Zhang +1
In this paper, we study efficient and robust computational methods for solving the security-constrained alternating current optimal power flow (SC-ACOPF) problem, a two-stage nonli…
Dual Descent ALM and ADMM
Kaizhao Sun, Andy Sun
Classical primal-dual algorithms attempt to solve by alternatively minimizing over the primal variable through primal descent and maximizing t…
Decomposition Methods for Global Solutions of Mixed-Integer Linear Programs
Kaizhao Sun, Mou Sun, Wotao Yin
This paper introduces two decomposition-based methods for two-block mixed-integer linear programs (MILPs), which aim to take advantage of separable structures of the original probl…
A two-level distributed algorithm for nonconvex constrained optimization
Kaizhao Sun, X. Andy Sun
This paper aims to develop distributed algorithms for nonconvex optimization problems with complicated constraints associated with a network. The network can be a physical one, suc…