2023/05/07 by Qi Liu, Joseph Y.J. Chow, Liu, Qi +1
Engineering · Social Sciences · #Computers and Society (cs.CY) #FOS: Computer and information sciences #FOS: Electrical engineering #Systems and Control (eess.SY) #Transportation Planning and Optimization #Transportation and Mobility Innovations #Vehicle Routing Optimization Methods #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2305.04324
openalex publication_date 2023/05/07 · openalex created_date 2023/05/10 · openalex updated_date 2026/07/28
A fast recovery from disruptions is of vital importance for the reliability of transit systems. This study presents a new attempt to tackle the transit disruption mitigation problem in a comprehensive and hierarchical way. A network level strategy selection optimization model is formulated as a joint routing and resource allocation (nJRRA) problem. By constraining the problem further into an epsilon-constrained nJRRA problem, classic solution algorithms can be applied to solve the quadratically constrained quadratic program (QCQP). On top of this "basic model", we propose adding a decision to delay the resource allocation decisions up to a maximum initiation time when the incident duration is stochastic. To test the models, a quasi-dynamic evaluation program with a given incident duration distribution is constructed using discretized time steps and discrete distributions. Five different demand patterns and four different disruption duration distributions (20 combinations) are tested on a toy transit network. The results show that the two models outperform benchmark strategies such as using only line level adjustment or only bus bridging. They also highlight conditions when delaying the decision is preferred.