23 citations · 45 across the 7 of their papers we have counts for
7 papers
Anytime-Feasible Gradient Descent for Constrained Optimization Under Gradient Uncertainty
Sina Sharifi, Jiarui Wang, Mahyar Fazlyab
Constrained optimization is central to many engineering systems in which decisions must satisfy strict safety and operational requirements, especially in real-time settings with li…
Model Predictive Path Integral Control as Preconditioned Gradient Descent
Mahyar Fazlyab, Sina Sharifi, Jiarui Wang
Model Predictive Path Integral (MPPI) control is a widely used sampling-based method for trajectory optimization, yet its convergence properties remain only partially understood. T…
Anytime-Feasible First-Order Optimization via Safe Sequential QCQP
Jiarui Wang, Mahyar Fazlyab
This paper presents the Safe Sequential Quadratically Constrained Quadratic Programming (SS-QCQP) algorithm, a first-order method for smooth inequality-constrained nonconvex optimi…
Actor-Critic Physics-informed Neural Lyapunov Control
Jiarui Wang, Mahyar Fazlyab
Designing control policies for stabilization tasks with provable guarantees is a long-standing problem in nonlinear control. A crucial performance metric is the size of the resulti…
ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution
Haoran Ye, Jiarui Wang, Zhiguang Cao +5
The omnipresence of NP-hard combinatorial optimization problems (COPs) compels domain experts to engage in trial-and-error heuristic design. The long-standing endeavor of design au…
GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time
Haoran Ye, Jiarui Wang, Helan Liang +3
The recent end-to-end neural solvers have shown promise for small-scale routing problems but suffered from limited real-time scaling-up performance. This paper proposes GLOP (Globa…
DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization
Haoran Ye, Jiarui Wang, Zhiguang Cao +2
Ant Colony Optimization (ACO) is a meta-heuristic algorithm that has been successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally, customizing ACO…