Solving a multi-trip VRP with real heterogeneous fleet and time windows based on ant colony optimization: an industrial case study. - Jihee Han; Arash Mozhdehi; Yunli Wang; Sun Sun 002; Xin Wang 004 (IWCTS@SIGSPATIAL, 2022)

Multi-task graph neural network for truck speed prediction under extreme weather conditions. - Reza Safarzadeh Ramhormozi; Arash Mozhdehi; Saeid Kalantari; Yunli Wang; Sun Sun 002; Xin Wang 004 (SIGSPATIAL/GIS, 2022)

Meta-GCN: A Dynamically Weighted Loss Minimization Method for Dealing with the Data Imbalance in Graph Neural Networks. - Mahdi Mohammadizadeh; Arash Mozhdehi; Yani Ioannou; Xin Wang 004 (Canadian AI, 2023)

Edge-DIRECT: A Deep Reinforcement Learning-based Method for Solving Heterogeneous Electric Vehicle Routing Problem with Time Window Constraints. - Arash Mozhdehi; Mahdi Mohammadizadeh; Xin Wang 004 (Canadian AI, 2024)

EFECTIW-ROTER: Deep Reinforcement Learning Approach for Solving Heterogeneous Fleet and Demand Vehicle Routing Problem With Time-Window Constraints. - Arash Mozhdehi; Mahdi Mohammadizadeh; Yunli Wang; Sun Sun 002; Xin Wang 004 (SIGSPATIAL/GIS, 2024)

SPADE: Solving the Multi-Depot Vehicle Routing Problem with Inter-Depot Routes Using Multi-Agent Deep Reinforcement Learning. - Arash Mozhdehi; Mahdi Mohammadizadeh; Saeid Kalantari; Beom Sae (Shawn) Kim; Xin Wang 004 (Canadian AI, 2025)

SED2AM: Solving Multi-Trip Time-Dependent Vehicle Routing Problem Using Deep Reinforcement Learning. - Arash Mozhdehi; Yunli Wang; Sun Sun 002; Xin Wang 004 (ACM Trans. Knowl. Discov. Data, 2025)

SED2AM: Solving Multi-Trip Time-Dependent Vehicle Routing Problem using Deep Reinforcement Learning. - Arash Mozhdehi; Yunli Wang; Sun Sun; Xin Wang (CoRR, 2025)