Abstract
On-Demand Mobility Services (ODMS) have gained considerable popularity over the past few years. Travelers use mobile phone applications to easily request a ride, update trip itinerary and pay the ride fare. This paper describes a novel methodology for integrated ride matching and vehicle routing for ODMS with ridesharing and transfer options. The methodology adopts a hybrid heuristic approach, which enables solving medium to large problem instances in near real-time. The solution of this problem will be a set of routes for vehicles and a ride match for each passenger. The heuristic (1) promptly responds to individual ride requests, and (2) periodically re-evaluates the generated solutions and recommend modifications to enhance the overall solution quality by increasing the number of served passengers and total profit of the system. The results of a set of experiments considering hypothetical and real-world networks show that the methodology can provide efficient solutions while satisfying the real-time execution requirements. In addition, the results show that the Transportation Network Company (TNC) could serve more passengers and achieve higher profitability if more passengers are willing to rideshare or transfer. Also, activating a rollback procedure increases the number of served passengers and associated profits.
Similar content being viewed by others
References
Agatz, N., Erera, A., Savelsbergh, M., Wang, X.: Dynamic ridesharing: a simulation study in metro-Atlanta. Proc. Soc. Behav. Sci. 17(1), 532–50 (2011)
Alonso-Mora, J., Samaranayake, S., Wallar, A., Frazzoli, E., Rus, D.: On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment. Proc. Nat. Acad. Sci. 114(3), 462–67 (2017)
Attanasio, A., Cordeau, F., Ghiani, G., Laporte, G.: Parallel tabu search heuristics for the dynamic multi-vehicle dial-a-ride problem. Parallel Comput. 30(3), 377–87 (2004)
Baldacci, R., Vittorio, M., Aristide, M.: An exact method for the carpooling problem based on Lagrangean column generation. Oper. Res. 52(3), 422–439 (2004)
Baldacci, R., Bartolini, E., Mingozzi, A.: An exact algorithm for the pickup and delivery problem with time windows. Oper. Res. 59(2), 414–26 (2011)
Baoxiang, L., Krushinsky, D., Woensel, T., Reijers, H.: An adaptive large neighborhood search heuristic for share-a-ride problem. Comput. Oper. Res. 66, 170–180 (2016)
Braekers, K., Caris, A., Janssens, K.: Exact and meta-heuristic approach for a general heterogeneous dial-a-ride problem with multiple depots. Trans. Res. B Methodol. 67, 166–186 (2014)
Calvo, W., De-Luigi, F., Haastrup, P., Maniezzo, V.: A distributed geographic information system for the daily carpooling problem. Comput. Oper. Res. 31(13), 2263–2278 (2004)
Cats, O., Kucharski, R., Danda, S. R., Yap, M.: Beyond the Dichotomy: How Ride-hailing Competes with and Complements Public Transport. arXiv preprint arXiv:2104.04208 (2021)
Cheikh, B., Tahon, C., Hammadi, S.: An evolutionary approach to solve the dynamic multihop ridematching problem. Simulation 93(1), 3–19 (2017)
Coltin, B., Veloso, M.: Ridesharing with passenger transfers. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (2014)
Cordeau, F.: A branch-and-cut algorithm for the dial-a-ride problem. Oper. Res. 54(3), 573–86 (2006)
Cordeau, F., Laporte, G., Savelsbergh, W., Vigo, D.: Vehicle Routing. Handbooks in Operations Research and Management Science, Vol. 14, pp. 367–428 (2007)
Coslovich, L., Pesenti, R., Ukovich, W.: A two-phase insertion technique of unexpected customers for a dynamic dial-a-ride problem. Eur. J. Oper. Res. 175(3), 1605–15 (2006)
Cozza, J.: The History of Carpooling. www.shareable.net/the-history-of-carpooling-from-jitneys-to-ridesharing. Accessed July 22 (2019)
DiFebbraro, A., Gattorna, E., Sacco, N.: Optimization of dynamic ridesharing systems. Transp. Res. Rec. 2359(1), 44–50 (2013)
Gendreau, M., Guertin, F., Potvin, Y., Seguin, R.: Neighborhood search heuristics for a dynamic vehicle dispatching problem with pickups and deliveries. Trans. Res. C Emerg. Technol. 14(3), 157–174 (2006)
Ghoseiri, K.: Dynamic rideshare optimized matching problem. Dissertation (2012)
Giuliano, G., Levine, D., Teal, R.: Impact of high occupancy vehicle lanes on carpooling behavior. Transportation 17(2), 159–177 (1990)
Herbawi, W., Weber, M.: Evolutionary multi-objective route planning in dynamic multi-hop ridesharing. In: European Conference on Evolutionary Computation in Combinatorial Optimization. Springer, Berlin (2011)
Hosni, H., Naoum-Sawaya, J., Artail, H.: The shared taxi problem: formulation and solution methods. Trans. Res. B Methodol. 70(1), 303–18 (2014)
Hou, Y., Li, X., Qiao, C.: TicTac: From transfer-incapable carpooling to transfer-allowed carpooling. In: 2012 IEEE Global Communications Conference (GLOBECOM), pp. 268–273 (2012)
Huang, C., Zhang, D., Si, Y.W., Leung, S.C.: Tabu search for the real-world carpooling problem. J. Combin. Optim. 32(2), 492–512 (2016)
Hyland, M., Mahmassani, H.: Dynamic autonomous vehicle fleet operations: optimization based strategies to assign AVs to immediate traveler demand requests. Trans. Res. C Emerg. Technol. 92, 278–297 (2018)
Iqbal, M.: Uber Revenue and Usage Statistics. www.businessofapps.com/data/uber-statistics. Accessed April 6, 2021
Jorgensen, M., Larsen, J., Bergvinsdottir, B.: Solving the dial-a-ride problem using genetic algorithms. J. Oper. Res. Soc. 58(10), 1321–31 (2007)
Li, X., Hu, S., Fan, W., Deng, K.: Modeling an enhanced ridesharing system with meet points and time windows. PloS one 13(5) (2018)
Lotfi, S., Abdelghany, K., Hashemi, H.: Modeling framework and decomposition scheme for on-demand mobility services with ridesharing and transfer. Comput. Aided Civ. Infrast. Eng. 34(1), 21–37 (2019)
Ma, C., He, R., Zhang, W.: Path optimization of taxi carpooling. PLoS One 13(8) (2018)
Mahmoudi, M., Zhou, X.: Finding optimal solutions for vehicle routing problem with pickup and delivery services with time windows: a dynamic programming approach based on state-space-time network representations. Trans. Res. B: Methodol. 89, 19–42 (2016)
Masoud, N., Jayakrishnan, R.: A real-time algorithm to solve the peer-to-peer ride-matching problem in a flexible ridesharing system. Transp. Res. B: Methodol. 106, 218–236 (2017)
Masson, R., Ropke, S., Lehuede, F., Peton, O.: A branch-and-cut-and-price approach for the pickup and delivery problem with shuttle routes. Eur. J. Oper. Res. 236(3), 849–62 (2014)
Mitrović-Minić, S., Laporte, G.: The pickup and delivery problem with time windows and transshipment. INFOR: Inf. Syst. Oper. Res. 44(3), 217–27 (2006)
Nam, D., Yang, D., An, S., Yu, G., Jayakrishnan, R., Masoud, N.: Designing a transit-feeder system using multiple sustainable modes: peer-to-peer (P2P) ridesharing, bike sharing, and walking. Transp. Res. Rec. 2672(8), 754–763 (2018)
Oh, S., Lentzakis, A.F., Seshadri, R., Ben-Akiva, M.: Impacts of automated mobility-on-demand on traffic dynamics, energy and emissions: a case study of Singapore. Simul. Model. Pract. Theory 110, 102327 (2021)
Ropke, S., Cordeau, F., Laporte, G.: Models and branch-and-cut algorithms for pickup and delivery problems with time windows. Networks 49(4), 258–72 (2007)
Soza-Parra, J., Kucharski, R., Cats, O.: Ride-pooling potential under alternative spatial demand patterns. arXiv preprint: arXiv:2104.04209 (2021)
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Lotfi, S., Abdelghany, K. Ride matching and vehicle routing for on-demand mobility services. J Heuristics 28, 235–258 (2022). https://doi.org/10.1007/s10732-022-09491-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10732-022-09491-7