41 citations · 75 across the 14 of their papers we have counts for
14 papers
Structured Nonsmooth Optimization Using Functional Encoding and Branching Information
Fengqiao Luo
We develop a novel gradient-based algorithm for optimizing nonsmooth nonconvex functions where nonsmoothness arises from explicit nonsmooth operators in the objective's analytical…
An Empirical Quantile Estimation Approach to Nonlinear Optimization Problems with Chance Constraints
Fengqiao Luo, Jeffrey Larson
We investigate an empirical quantile estimation approach to solve chance-constrained nonlinear optimization problems. Our approach is based on the reformulation of the chance const…
Coordinated Vehicle Platooning on Tree Networks: Efficient Time Discretization and Strengthened Formulation
Fengqiao Luo
We consider the coordinated vehicle platooning problem on a tree network with time constraints while the routes of vehicles are given. The problem is to coordinate the departure ti…
Polyhedral Analysis of a Polytope from a Service Center Location Problem with a Type of Decision-Dependent Customer Demand
Fengqiao Luo
The polytope from a service center location problem with a special location-dependent demand has been investigated in this paper. The location-dependent demand is defined based on…
A Cutting-plane and Benders' Decomposition Algorithm for Two-Stage Distributionally Robust Convex programs
Fengqiao Luo, Shibshankar Dey, Sanjay Mehrotra
We present a finitely convergent cutting-plane algorithm for solving a general mixed-integer convex program given an oracle for solving a general convex program. This method is ext…
A Distributionally-Robust Service Center Location Problem with Decision Dependent Demand Induced from a Maximum Attraction Principle
Fengqiao Luo
We establish and analyze a service center location model with a simple but novel decision-dependent demand induced from a maximum attraction principle. The model formulations are i…
A Model of Supply-Chain Decisions for Resource Sharing with an Application to Ventilator Allocation to Combat COVID-19
Sanjay Mehrotra, Hamed Rahimian, Masoud Barah +2
This paper presents a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different t…
A Repeated Route-then-Schedule Approach to Coordinated Vehicle Platooning: Algorithms, Valid Inequalities and Computation
Fengqiao Luo, Jeffrey Larson
Platooning of vehicles is a promising approach for reducing fuel consumption, increasing vehicle safety, and using road space more efficiently. We consider the important but diffic…
A Geometric Branch and Bound Method for a Class of Robust Maximization Problems of Convex Functions
Fengqiao Luo, Sanjay Mehrotra
We investigate robust optimization problems defined for maximizing convex functions. For finite uncertainty set, we develop a geometric branch-and-bound algorithmic approach to sol…
A Decomposition Method for Distributionally-Robust Two-stage Stochastic Mixed-integer Cone Programs
Fengqiao Luo, Sanjay Mehrotra
We develop a decomposition algorithm for distributionally-robust two-stage stochastic mixed-integer convex cone programs, and its important special case of distributionally-robust…
Service Center Location with Decision Dependent Utilities with an Application to Early Stage Testing and Vaccination in Epidemic Planning
Fengqiao Luo, Sanjay Mehrotra
We study a service center location problem with ambiguous utility gains upon receiving service. The model is motivated by the problem of deciding medical clinic/service centers, po…
Distributionally Robust Optimization with Decision Dependent Ambiguity Sets
Fengqiao Luo, Sanjay Mehrotra
We study decision dependent distributionally robust optimization models, where the ambiguity sets of probability distributions can depend on the decision variables. These models ar…
A Concentration Result of Estimating Phi-Divergence using Data Dependent Partition
Fengqiao Luo, Sanjay Mehrotra
Estimation of the -divergence between two unknown probability distributions using empirical data is a fundamental problem in information theory and statistical learning. We cons…
Decomposition Algorithm for Distributionally Robust Optimization using Wasserstein Metric
Fengqiao Luo, Sanjay Mehrotra
We study distributionally robust optimization (DRO) problems where the ambiguity set is defined using the Wasserstein metric. We show that this class of DRO problems can be reformu…