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math.OC2025
Individual Path Recommendation Under Public Transit Service Disruptions Considering Behavior Uncertainty
Baichuan Mo, Haris N. Koutsopoulos, Zuo-Jun Max Shen +1
Public transit passengers need guidance during service disruptions. This study proposes an individual-based path (IPR) recommendation model. The model decides which paths to recomm…
math.OC2025
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…
math.OC2025
Robust Path Recommendations During Public Transit Disruptions Under Demand Uncertainty
Baichuan Mo, Haris N. Koutsopoulos, Max Zuo-Jun Shen +1
When there are significant service disruptions in public transit systems, passengers usually need guidance to find alternative paths. This paper proposes a path recommendation mode…