Stable matching mechanism for multi-modal integration on mobility-as-a-service platformOA

In mobility-as-a-service(MaaS)platforms integrating ridesharing with public transit,each rider-driver pair may have multiple potential matches via different transfer nodes,with users being self-interested with heterogeneous preferences.After generating all feasible integrated matches,a two-sided one-to-one stable matching model is formulated to maximize platform revenue,where each feasible match corresponds to a stability constraint embedding preference information.To solve this model efficiently,an iterative constraint-generation algorithm is designed.It repeatedly solves a restricted master problem to obtain a temporary solution and a subproblem to identify violated stability constraints,iterating until no violations remain.The proposed algorithm can significantly improve computational efficiency.Compared with a centralized matching benchmark with the blocking rate up to 75%,stable matching increases transit usage and user acceptance at the cost of a 31.43% reduction in average platform revenue.Riders experience longer detours with greater cost savings,whereas drivers exhibit the opposite pattern.