RL-MSA: a Reinforcement Learning-based Multi-line bus Scheduling Approach

arXiv:2403.06466v1 Announce Type: new
Abstract: Multiple Line Bus Scheduling Problem (MLBSP) is vital to save operational cost of bus company and guarantee service quality for passengers. Existing approaches typically generate a bus scheduling scheme in an offline manner and then schedule buses according to the scheme. In practice, uncertain events such as traffic congestion occur frequently, which may make the pre-determined bus scheduling scheme infeasible. In this paper, MLBSP is modeled as a Markov Decision Process (MDP). A Reinforcement Learning-based …

abstract arxiv cost cs.ai cs.lg events generate line multiple offline practice quality reinforcement reinforcement learning save scheduling service type uncertain vital