IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v186y2024ics0191261524001358.html
   My bibliography  Save this article

A Branch-and-Price algorithm for the electric autonomous Dial-A-Ride Problem

Author

Listed:
  • Su, Yue
  • Dupin, Nicolas
  • Parragh, Sophie N.
  • Puchinger, Jakob

Abstract

The Electric Autonomous Dial-A-Ride Problem (E-ADARP) consists in scheduling a fleet of electric autonomous vehicles to provide ride-sharing services for customers that specify their origins and destinations. The E-ADARP considers the following perspectives: (i) a weighted-sum objective that minimizes both total travel time and total excess user ride time; (ii) the employment of electric autonomous vehicles and a partial recharging policy. This paper presents the first labeling algorithm for a path-based formulation of the DARP/E-ADARP, where the main ingredient includes: (1) fragment-based representation of paths, (2) a novel approach that abstracts fragments to arcs while ensuring excess-user-ride-time optimality, (3) construction of a sparser new graph with the abstracted arcs, which is proven to preserve all feasible routes of the original graph, and (4) strong dominance rules and constant-time feasibility checks to compute the shortest paths efficiently. This labeling algorithm is then integrated into Branch-and-Price (B&P) algorithms to solve the E-ADARP. In the computational experiments, the B&P algorithm achieves optimality in 71 out of 84 instances. Remarkably, among these instances, 50 were solved optimally at the root node without branching. We identify 26 new best solutions, improve 30 previously reported lower bounds, and provide 17 new lower bounds for large-scale instances with up to 8 vehicles and 96 requests. In total 42 new best solutions are generated on previously solved and unsolved instances. In addition, we analyze the impact of incorporating the total excess user ride time within the objectives and allowing unlimited visits to recharging stations. The following managerial insights are provided: (1) solving a weighted-sum objective function can significantly enhance the service quality, while still maintaining operational costs at nearly optimal levels, (2) the relaxation on charging visits allows us to solve all instances feasibly and further reduces the average solution cost.

Suggested Citation

  • Su, Yue & Dupin, Nicolas & Parragh, Sophie N. & Puchinger, Jakob, 2024. "A Branch-and-Price algorithm for the electric autonomous Dial-A-Ride Problem," Transportation Research Part B: Methodological, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:transb:v:186:y:2024:i:c:s0191261524001358
    DOI: 10.1016/j.trb.2024.103011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261524001358
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.trb.2024.103011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    2. Timo Gschwind & Stefan Irnich, 2015. "Effective Handling of Dynamic Time Windows and Its Application to Solving the Dial-a-Ride Problem," Transportation Science, INFORMS, vol. 49(2), pages 335-354, May.
    3. Martin Desrochers & Jacques Desrosiers & Marius Solomon, 1992. "A New Optimization Algorithm for the Vehicle Routing Problem with Time Windows," Operations Research, INFORMS, vol. 40(2), pages 342-354, April.
    4. Ho, Sin C. & Szeto, W.Y. & Kuo, Yong-Hong & Leung, Janny M.Y. & Petering, Matthew & Tou, Terence W.H., 2018. "A survey of dial-a-ride problems: Literature review and recent developments," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 395-421.
    5. Cordeau, Jean-François & Laporte, Gilbert, 2003. "A tabu search heuristic for the static multi-vehicle dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 37(6), pages 579-594, July.
    6. Guy Desaulniers & François Lessard & Ahmed Hadjar, 2008. "Tabu Search, Partial Elementarity, and Generalized k -Path Inequalities for the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 42(3), pages 387-404, August.
    7. Guy Desaulniers & Fausto Errico & Stefan Irnich & Michael Schneider, 2016. "Exact Algorithms for Electric Vehicle-Routing Problems with Time Windows," Operations Research, INFORMS, vol. 64(6), pages 1388-1405, December.
    8. Bongiovanni, Claudia & Kaspi, Mor & Geroliminis, Nikolas, 2019. "The electric autonomous dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 436-456.
    9. Jean-François Cordeau, 2006. "A Branch-and-Cut Algorithm for the Dial-a-Ride Problem," Operations Research, INFORMS, vol. 54(3), pages 573-586, June.
    10. Mads Jepsen & Bjørn Petersen & Simon Spoorendonk & David Pisinger, 2008. "Subset-Row Inequalities Applied to the Vehicle-Routing Problem with Time Windows," Operations Research, INFORMS, vol. 56(2), pages 497-511, April.
    11. Jean-François Cordeau & Gilbert Laporte, 2007. "The dial-a-ride problem: models and algorithms," Annals of Operations Research, Springer, vol. 153(1), pages 29-46, September.
    12. Timo Gschwind & Michael Drexl, 2019. "Adaptive Large Neighborhood Search with a Constant-Time Feasibility Test for the Dial-a-Ride Problem," Transportation Science, INFORMS, vol. 53(2), pages 480-491, March.
    13. Alberto Ceselli & Ángel Felipe & M. Teresa Ortuño & Giovanni Righini & Gregorio Tirado, 2021. "A Branch-and-Cut-and-Price Algorithm for the Electric Vehicle Routing Problem with Multiple Technologies," SN Operations Research Forum, Springer, vol. 2(1), pages 1-33, March.
    14. Guy Desaulniers & Timo Gschwind & Stefan Irnich, 2020. "Variable Fixing for Two-Arc Sequences in Branch-Price-and-Cut Algorithms on Path-Based Models," Transportation Science, INFORMS, vol. 54(5), pages 1526-5447, September.
    15. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    16. Hiermann, Gerhard & Hartl, Richard F. & Puchinger, Jakob & Vidal, Thibaut, 2019. "Routing a mix of conventional, plug-in hybrid, and electric vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 235-248.
    17. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert & Veneroni, Marco, 2017. "Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 158-187.
    18. Niklas Kohl & Jacques Desrosiers & Oli B. G. Madsen & Marius M. Solomon & François Soumis, 1999. "2-Path Cuts for the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 33(1), pages 101-116, February.
    19. Ali Mehsin Alyasiry & Michael Forbes & Michael Bulmer, 2019. "An Exact Algorithm for the Pickup and Delivery Problem with Time Windows and Last-in-First-out Loading," Transportation Science, INFORMS, vol. 53(6), pages 1695-1705, November.
    20. Felipe, Ángel & Ortuño, M. Teresa & Righini, Giovanni & Tirado, Gregorio, 2014. "A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 111-128.
    21. Braekers, Kris & Caris, An & Janssens, Gerrit K., 2014. "Exact and meta-heuristic approach for a general heterogeneous dial-a-ride problem with multiple depots," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 166-186.
    22. Montoya, Alejandro & Guéret, Christelle & Mendoza, Jorge E. & Villegas, Juan G., 2017. "The electric vehicle routing problem with nonlinear charging function," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 87-110.
    23. Schneider, M. & Stenger, A. & Goeke, D., 2014. "The Electric Vehicle Routing Problem with Time Windows and Recharging Stations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62382, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    24. Su, Yue & Dupin, Nicolas & Puchinger, Jakob, 2023. "A deterministic annealing local search for the electric autonomous dial-a-ride problem," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1091-1111.
    25. Masmoudi, Mohamed Amine & Hosny, Manar & Demir, Emrah & Genikomsakis, Konstantinos N. & Cheikhrouhou, Naoufel, 2018. "The dial-a-ride problem with electric vehicles and battery swapping stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 392-420.
    26. Bongiovanni, Claudia & Kaspi, Mor & Cordeau, Jean-François & Geroliminis, Nikolas, 2022. "A machine learning-driven two-phase metaheuristic for autonomous ridesharing operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Su, Yue & Dupin, Nicolas & Puchinger, Jakob, 2023. "A deterministic annealing local search for the electric autonomous dial-a-ride problem," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1091-1111.
    2. Masmoudi, Mohamed Amine & Hosny, Manar & Demir, Emrah & Genikomsakis, Konstantinos N. & Cheikhrouhou, Naoufel, 2018. "The dial-a-ride problem with electric vehicles and battery swapping stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 392-420.
    3. Schulz, Arne & Pfeiffer, Christian, 2024. "Using fixed paths to improve branch-and-cut algorithms for precedence-constrained routing problems," European Journal of Operational Research, Elsevier, vol. 312(2), pages 456-472.
    4. Zhang, Li & Liu, Zhongshan & Yu, Lan & Fang, Ke & Yao, Baozhen & Yu, Bin, 2022. "Routing optimization of shared autonomous electric vehicles under uncertain travel time and uncertain service time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    5. Bongiovanni, Claudia & Kaspi, Mor & Geroliminis, Nikolas, 2019. "The electric autonomous dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 436-456.
    6. Gaul, Daniela & Klamroth, Kathrin & Stiglmayr, Michael, 2022. "Event-based MILP models for ridepooling applications," European Journal of Operational Research, Elsevier, vol. 301(3), pages 1048-1063.
    7. Cortés-Murcia, David L. & Prodhon, Caroline & Murat Afsar, H., 2019. "The electric vehicle routing problem with time windows, partial recharges and satellite customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 184-206.
    8. Zhang, Li & Liu, Zhongshan & Yu, Bin & Long, Jiancheng, 2024. "A ridesharing routing problem for airport riders with electric vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    9. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    10. Dönmez, Sercan & Koç, Çağrı & Altıparmak, Fulya, 2022. "The mixed fleet vehicle routing problem with partial recharging by multiple chargers: Mathematical model and adaptive large neighborhood search," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    11. Stefan Faldum & Timo Gschwind & Stefan Irnich, 2023. "Subset-Row Inequalities and Unreachability in Path-based Formulations for Routing and Scheduling Problems," Working Papers 2310, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    12. Bongiovanni, Claudia & Kaspi, Mor & Cordeau, Jean-François & Geroliminis, Nikolas, 2022. "A machine learning-driven two-phase metaheuristic for autonomous ridesharing operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    13. Timo Gschwind & Stefan Irnich, 2012. "Effective Handling of Dynamic Time Windows and Synchronization with Precedences for Exact Vehicle Routing," Working Papers 1211, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    14. LIAN, Ying & LUCAS, Flavien & SÖRENSEN, Kenneth, 2022. "The electric on-demand bus routing problem with partial charging and nonlinear functions," Working Papers 2022005, University of Antwerp, Faculty of Business and Economics.
    15. Sadati, Mir Ehsan Hesam & Çatay, Bülent, 2021. "A hybrid variable neighborhood search approach for the multi-depot green vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    16. Schiffer, Maximilian & Walther, Grit, 2018. "Strategic planning of electric logistics fleet networks: A robust location-routing approach," Omega, Elsevier, vol. 80(C), pages 31-42.
    17. Christian Tilk & Ann-Kathrin Rothenbächer & Timo Gschwind & Stefan Irnich, 2016. "Asymmetry Helps: Dynamic Half-Way Points for Solving Shortest Path Problems with Resource Constraints Faster," Working Papers 1615, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    18. Johnsen, Lennart C. & Meisel, Frank, 2022. "Interrelated trips in the rural dial-a-ride problem with autonomous vehicles," European Journal of Operational Research, Elsevier, vol. 303(1), pages 201-219.
    19. Zhang, Shuai & Gajpal, Yuvraj & Appadoo, S.S. & Abdulkader, M.M.S., 2018. "Electric vehicle routing problem with recharging stations for minimizing energy consumption," International Journal of Production Economics, Elsevier, vol. 203(C), pages 404-413.
    20. Tilk, Christian & Rothenbächer, Ann-Kathrin & Gschwind, Timo & Irnich, Stefan, 2017. "Asymmetry matters: Dynamic half-way points in bidirectional labeling for solving shortest path problems with resource constraints faster," European Journal of Operational Research, Elsevier, vol. 261(2), pages 530-539.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:186:y:2024:i:c:s0191261524001358. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.