7 papers
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…
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…
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…
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…
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…
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…