A hybrid large neighborhood search algorithm for the integrated dial-a-ride problem using electric vehicles
Yumeng Fang, Tai-Yu Ma

TL;DR
This paper presents a hybrid metaheuristic algorithm for solving the integrated dial-a-ride problem with electric vehicles, optimizing operational costs and customer travel time while considering charging and transfer constraints.
Contribution
It introduces a novel hybrid large neighborhood search algorithm specifically designed for electric vehicle-based integrated dial-a-ride systems, addressing complex routing and charging challenges.
Findings
Solution quality improved by 23.8% over baseline within 2 minutes
Algorithm outperforms state-of-the-art solver with 8-hour limit
System benefits are more pronounced in dense transit areas
Abstract
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…
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Taxonomy
TopicsTransportation and Mobility Innovations · Vehicle Routing Optimization Methods · Electric Vehicles and Infrastructure
