A hybrid large neighborhood search algorithm for the integrated dial-a-ride problem using electric vehicles

Integrating demand-responsive mobility services with transit systems is recognized as a practical and effective strategy to mitigate their impact on traffic congestion and the environment. This study develops an efficient hybrid metaheuristic to solve the integrated dial-a-ride problem by utilizing electric vehicles to minimize operational costs and customer travel time. Customer transfer inconvenience is restricted by a maximum intermodal transfer time to synchronize demand-responsive buses’ arrival and transit departures. The proposed metaheuristic addresses the challenges of integrating demand-responsive vehicle routing and charging operations with fixed-route transit systems with capacitated charging stations and partial recharge. We benchmarked our algorithm against a state-of-the-art mixed-integer programming solver on instances with 10–50 customers and two transit lines. Our approach achieves solutions that are, on average, 23.8% better in solution quality within around 2 min, outperforming those obtained by the solver using an 8-hour computational time limit. We evaluate the impact of various system parameters to bridge the gap between theory and practice. The results suggest that, from the operator’s perspective, while the integrated dial-a-ride service reduces vehicle kilometers traveled, the used fleet size may not necessarily be reduced when ensuring high-quality service for passengers. Moreover, operating the integrated systems is more beneficial in areas with dense transit networks, compared with increases in transit frequency. The findings provide valuable insights for developing integrated dial-a-ride services in practice.