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Xiaolei Ma
Researcher at Beihang University
Publications - 83
Citations - 8640
Xiaolei Ma is an academic researcher from Beihang University. The author has contributed to research in topics: Deep learning & Vehicle routing problem. The author has an hindex of 29, co-authored 83 publications receiving 5977 citations. Previous affiliations of Xiaolei Ma include Chinese Ministry of Public Security & University of Washington.
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Two-echelon logistics distribution region partitioning problem based on a hybrid particle swarm optimization-genetic algorithm
TL;DR: A model to minimize the total cost of the two-echelon logistics distribution network is established and the EPSO-GA algorithm is superior to the other three algorithms, Hybrid Particle Swarm Optimization, GA, and Ant Colony Optimization in terms of the partitioning schemes, total cost and number of iterations.
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Headway-based bus bunching prediction using transit smart card data
TL;DR: A predictive framework to capture the stop-level headway irregularity based on transit smart card data can provide timely and accurate information for potential bus bunching prevention and inform passengers when the next bus will arrive and will greatly increase transit ridership and reduce operating costs for transit authorities.
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DRIVE Net: E-Science Transportation Platform for Data Sharing, Visualization, Modeling, and Analysis
TL;DR: A framework is proposed for a regionwide web-based transportation decision system that adopts digital roadway maps as the base and provides data layers for integrating multiple data sources (e.g., traffic sensor, incident, accident, and travel time).
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Probabilistic Prediction of Bus Headway Using Relevance Vector Machine Regression
TL;DR: With the probabilistic bus headway prediction information, transit riders can better schedule their trips to avoid late and early arrivals at bus stops, while transit operators can adopt the targeted correction actions to maintain regular headway for bus bunching prevention.
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Improving flex-route transit services with modular autonomous vehicles
Xiaohan Liu,Xiaobo Qu,Xiaolei Ma +2 more
TL;DR: A novel operational design for flex-route transit services to reduce operation costs of vehicles and improve the service quality of customers is presented, formulated as a mixed-integer linear program that is NP-hard.