9 citations · 24 across the 12 of their papers we have counts for
12 papers
Randomized methods for computing optimal transport without regularization and their convergence analysis
Yue Xie, Zhongjian Wang, Zhiwen Zhang
The optimal transport (OT) problem can be reduced to a linear programming (LP) problem through discretization. In this paper, we introduced the random block coordinate descent (RBC…
Evolutionary Algorithms for Limiting the Effect of Uncertainty for the Knapsack Problem with Stochastic Profits
Aneta Neumann, Yue Xie, Frank Neumann
Evolutionary algorithms have been widely used for a range of stochastic optimization problems in order to address complex real-world optimization problems. We consider the knapsack…
Heuristic Strategies for Solving Complex Interacting Large-Scale Stockpile Blending Problems
Yue Xie, Aneta Neumann, Frank Neumann
The Stockpile blending problem is an important component of mine production scheduling, where stockpiles are used to store and blend raw material. The goal of blending material fro…
Complexity of a Projected Newton-CG Method for Optimization with Bounds
Yue Xie, Stephen J. Wright
This paper describes a method for solving smooth nonconvex minimization problems subject to bound constraints with good worst-case complexity guarantees and practical performance.…
Runtime Analysis of RLS and the (1+1) EA for the Chance-constrained Knapsack Problem with Correlated Uniform Weights
Yue Xie, Aneta Neumann, Frank Neumann +1
Addressing a complex real-world optimization problem is a challenging task. The chance-constrained knapsack problem with correlated uniform weights plays an important role in the c…
Heuristic Strategies for Solving Complex Interacting Stockpile Blending Problem with Chance Constraints
Yue Xie, Aneta Neumann, Frank Neumann
Heuristic algorithms have shown a good ability to solve a variety of optimization problems. Stockpile blending problem as an important component of the mine scheduling problem is a…
Specific Single- and Multi-Objective Evolutionary Algorithms for the Chance-Constrained Knapsack Problem
Yue Xie, Aneta Neumann, Frank Neumann
The chance-constrained knapsack problem is a variant of the classical knapsack problem where each item has a weight distribution instead of a deterministic weight. The objective is…
Evolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives
Hirad Assimi, Oscar Harper, Yue Xie +2
Real-world combinatorial optimization problems are often stochastic and dynamic. Therefore, it is essential to make optimal and reliable decisions with a holistic approach. In this…
Complexity of Proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints
Yue Xie, Stephen J. Wright
We analyze worst-case complexity of a Proximal augmented Lagrangian (Proximal AL) framework for nonconvex optimization with nonlinear equality constraints. When an approximate firs…
SI-ADMM: A Stochastic Inexact ADMM Framework for Stochastic Convex Programs
Yue Xie, Uday V. Shanbhag
We consider the structured stochastic convex program requiring the minimization of subject to the constraint . Mo…
Tractable ADMM Schemes for Computing KKT Points and Local Minimizers for -Minimization Problems
Yue Xie, Uday V. Shanbhag
We consider an -minimization problem where is minimized over a polyhedral set and the -norm regularizer implicitly emphasizes sparsity of the solu…
On robust solutions to uncertain linear complementarity problems and their variants
Yue Xie, Uday V. Shanbhag
A popular approach for addressing uncertainty in variational inequality problems is by solving the expected residual minimization (ERM) problem. This avenue necessitates distributi…