activity
20162026
most citedDistributionally Robust Stochastic Optimization with Wasserstein Distance

96 citations · 147 across the 13 of their papers we have counts for

collaborators

15 papers

math.OC2026

Optimal Spectral Design with Prior Information

Anton J. Kleywegt, Johannes Milz, Mohit Singh +1

We study a class of spectral design problems in which a prior positive semidefinite information matrix is updated by a sum of rank-one matrices constructed from chosen design vecto…

math.OC2026

Policies for the Operation of an Ambulance Fleet under Uncertainty based on a New Preparedness Metric

Vincent Guigues, Anton Kleywegt, Victor Hugo Nascimento

Two important decisions in the management of an ambulance fleet are ambulance selection decisions and ambulance reassignment decisions. Ambulance selection decisions determine what…

stat.ME2024

Estimation of Spatiotemporal Poisson Processes with Some Missing Location Data

Vincent Guigues, Anton Kleywegt, Victor Hugo Nascimento +1

We consider models for spatiotemporal Poisson processes with some missing location data. We discuss four models that make provision for missing location data, and their estimation.…

math.OC2024

New Heuristics for the Operation of an Ambulance Fleet under Uncertainty

Vincent Guigues, Anton J. Kleywegt, Victor Hugo Nascimento

The operation of an ambulance fleet involves ambulance selection decisions about which ambulance to dispatch to each emergency, and ambulance reassignment decisions about what each…

cs.HC2024

Management and Visualization Tools for Emergency Medical Services

Vincent Guigues, Anton Kleywegt, Victor Hugo Nascimento +3

This paper describes an online tool for the visualization of medical emergency locations, randomly generated sample paths of medical emergencies, and the animation of ambulance mov…

stat.CO2024

LASPATED: A Library for the Analysis of Spatio-Temporal Discrete Data (User Manual)

Vincent Guigues, Anton J. Kleywegt, Giovanni Amorim +2

This is the User Manual of the LASPATED library. This library is available on GitHub (at https://github.com/vguigues/LASPATED)) and provides a set of tools to analyze spatiotempora…

stat.ME2024

LASPATED: a Library for the Analysis of SPAtio-TEmporal Discrete data

Vincent Guigues, Anton Kleywegt, Giovanni Amorim +2

We describe methods, tools, and a software library called LASPATED, available on GitHub (at https://github.com/vguigues/) to fit models using spatio-temporal data and space-time di…

math.OC2022★ 3 cited

Revenue Management Under the Markov Chain Choice Model with Joint Price and Assortment Decisions

Anton J. Kleywegt, Hongzhang Shao

Finding the optimal product prices and product assortment are two fundamental problems in revenue management. Usually, a seller needs to jointly determine the prices and assortment…

math.OC2022★ 1 cited

Operation of an ambulance fleet under uncertainty

Vincent Guigues, Anton Kleywegt, Victor Hugo Nascimento

We introduce two new optimization models for the dispatch of ambulances. The first model, called the ambulance selection problem, is used when an emergency call arrives to decide w…

math.OC2021★ 3 cited

Optimizing Pricing, Repositioning, En-Route Time, and Idle Time in Ride-Hailing Systems

Anton J. Kleywegt, Hongzhang Shao

In ride-hailing systems, en-route time refers to the time that elapses from the moment a car is dispatched to pick up a rider until the rider is picked up. A fundamental phenomenon…

math.OC2020★ 1 cited

Tractable Profit Maximization over Multiple Attributes under Discrete Choice Models

Hongzhang Shao, Anton J. Kleywegt

A fundamental problem in revenue management is to optimally choose the attributes of products, such that the total profit or revenue or market share is maximized. Usually, these at…

math.OC2020

Joint Estimation of Discrete Choice Model and Arrival Rate with Unobserved Stock-out Events

Hongzhang Shao, Anton J. Kleywegt

This paper studies the joint estimation problem of a discrete choice model and the arrival rate of potential customers when unobserved stock-out events occur. In this paper, we gen…

cs.LG2017★ 12 cited

Wasserstein Distributionally Robust Optimization and Variation Regularization

Rui Gao, Xi Chen, Anton J. Kleywegt

Wasserstein distributionally robust optimization (DRO) has recently achieved empirical success for various applications in operations research and machine learning, owing partly to…

math.OC2017★ 31 cited

Distributionally Robust Stochastic Optimization with Dependence Structure

Rui Gao, Anton J. Kleywegt

Distributionally robust stochastic optimization (DRSO) is a framework for decision-making problems under certainty, which finds solutions that perform well for a chosen set of prob…

math.OC2016★ 96 cited

Distributionally Robust Stochastic Optimization with Wasserstein Distance

Rui Gao, Anton J. Kleywegt

Distributionally robust stochastic optimization (DRSO) is an approach to optimization under uncertainty in which, instead of assuming that there is a known true underlying probabil…