32 citations · 104 across the 16 of their papers we have counts for
19 papers
FrontierOR: Benchmarking LLMs' Capacity for Efficient Algorithm Design in Large-Scale Optimization
Minwei Kong, Chonghe Jiang, Ao Qu +24
Large language models (LLMs) are increasingly used for optimization modeling and solver-code generation, yet practical operations research and optimization problems often require a…
AlphaOPT: Formulating Optimization Programs with Self-Improving LLM Experience Library
Minwei Kong, Ao Qu, Xiaotong Guo +12
Optimization modeling underlies critical decision-making across industries, yet remains difficult to automate: natural-language problem descriptions must be translated into precise…
Robust Vehicle Rebalancing with Deep Uncertainty in Autonomous Mobility-on-Demand Systems
Xinling Li, Xiaotong Guo, Qingyi Wang +2
Autonomous Mobility-on-Demand (AMoD) services offer an opportunity for improving passenger service while reducing pollution and energy consumption through effective vehicle coordin…
Mitigating Spatial Disparity in Urban Prediction Using Residual-Aware Spatiotemporal Graph Neural Networks: A Chicago Case Study
Dingyi Zhuang, Hanyong Xu, Xiaotong Guo +3
Urban prediction tasks, such as forecasting traffic flow, temperature, and crime rates, are crucial for efficient urban planning and management. However, existing Spatiotemporal Gr…
Journey-Based Transit Equity Analysis: A Case Study in the Greater Boston Area
Daniela Shuman, Xiaotong Guo, Nicholas S. Caros
In this paper, a new methodology, journey-based equity analysis, is presented for measuring the equity of transit convenience between income groups. Two data sources are combined i…
Advancing Transportation Mode Share Analysis with Built Environment: Deep Hybrid Models with Urban Road Network
Dingyi Zhuang, Qingyi Wang, Yunhan Zheng +4
Transportation mode share analysis is important to various real-world transportation tasks as it helps researchers understand the travel behaviors and choices of passengers. A typi…
Design of Transit-Centric Multimodal Urban Mobility System with Autonomous Mobility-on-Demand
Xiaotong Guo, Jinhua Zhao
This paper addresses the pressing challenge of urban mobility in the context of growing urban populations, changing demand patterns for urban mobility, and emerging technologies li…
ITINERA: Integrating Spatial Optimization with Large Language Models for Open-domain Urban Itinerary Planning
Yihong Tang, Zhaokai Wang, Ao Qu +11
Citywalk, a recently popular form of urban travel, requires genuine personalization and understanding of fine-grained requests compared to traditional itinerary planning. In this p…
Robust Binary and Multinomial Logit Models for Classification with Data Uncertainties
Baichuan Mo, Yunhan Zheng, Xiaotong Guo +2
Binary logit (BNL) and multinomial logit (MNL) models are the two most widely used discrete choice models for travel behavior modeling and prediction. However, in many scenarios, t…
Fairness-Enhancing Vehicle Rebalancing in the Ride-hailing System
Xiaotong Guo, Hanyong Xu, Dingyi Zhuang +2
The rapid growth of the ride-hailing industry has revolutionized urban transportation worldwide. Despite its benefits, equity concerns arise as underserved communities face limited…
Large Language Models for Travel Behavior Prediction
Baichuan Mo, Hanyong Xu, Ruoyun Ma +4
Travel behavior prediction is a core problem in transportation demand management and is traditionally addressed using numerical models calibrated on observed data. With recent adva…
The impacts of remote work on travel: insights from nearly three years of monthly surveys
Nicholas S. Caros, Xiaotong Guo, Yunhan Zheng +1
Remote work has expanded dramatically since 2020, upending longstanding travel patterns and behavior. More fundamentally, the flexibility for remote workers to choose when and wher…
Quantifying the uneven efficiency benefits of ridesharing market integration
Xiaohan Wang, Zhan Zhao, Hongmou Zhang +2
Ridesharing is recognized as one of the key pathways to sustainable urban mobility. With the emergence of Transportation Network Companies (TNCs) such as Uber and Lyft, the ridesha…
Predicting Drivers' Route Trajectories in Last-Mile Delivery Using A Pair-wise Attention-based Pointer Neural Network
Baichuan Mo, Qing Yi Wang, Xiaotong Guo +2
In last-mile delivery, drivers frequently deviate from planned delivery routes because of their tacit knowledge of the road and curbside infrastructure, customer availability, and…
Economies and Diseconomies of Scale in Segmented Mobility Sharing Markets
Hongmou Zhang, Xiaotong Guo, Jinhua Zhao
On-demand mobility sharing, provided by one or several transportation network companies (TNCs), is realized by real-time optimization algorithms to connect trips among tens of thou…
Transit Frequency Setting Problem with Demand Uncertainty
Xiaotong Guo, Baichuan Mo, Haris N. Koutsopoulos +2
Public transit systems are the backbone of urban mobility systems in the era of urbanization. The design of transit schedules is important for the efficient and sustainable operati…
Dissolving the Segmentation of a Shared Mobility Market: A Framework and Four Market Structure Designs
Xiaotong Guo, Ao Qu, Hongmou Zhang +2
In the governance of the shared mobility market of a city or of a metropolitan area, there are two conflicting principles: 1) the healthy competition between multiple platforms, su…
The emerging spectrum of flexible work locations: implications for travel demand and carbon emissions
Nicholas S. Caros, Xiaotong Guo, Jinhua Zhao
Many studies of the effect of remote work on travel demand assume that remote work takes place entirely at home. Recent evidence, however, shows that in the United States, remote w…
Shareability Network Based Decomposition Approach for Solving Large-scale Single School Routing Problems
Xiaotong Guo, Samitha Samaranayake
We consider the Single School Routing Problem (SSRP) where students from a single school are picked up by a fleet of school buses, subject to a set of constraints. The constraints…