IDEAS home Printed from https://ideas.repec.org/a/kap/netspa/v17y2017i3d10.1007_s11067-017-9358-x.html
   My bibliography  Save this article

Multicriteria Stochastic Shortest Path Problem for Electric Vehicles

Author

Listed:
  • Ehsan Jafari

    (The University of Texas at Austin)

  • Stephen D. Boyles

    (The University of Texas at Austin)

Abstract

This paper formulates the reliable routing of electric vehicles in stochastic networks as a multicriteria shortest path problem with travel time and charging cost components. The reliability term is defined as the probability of finishing the trip without running out of charge. The arc travel times are represented as stochastic variables, and arc energy consumption is modeled as a linear function of arc length and arc travel time. The traveler aims to minimize the generalized cost, formulated as a linear function of travel time and charging cost, subject to a minimum reliability threshold, representing the level of risk a traveler is willing to take in favor of routes with lower cost. We propose a solution algorithm based on generalized dynamic programming and show that the optimal solution may include cycles that visit at least one charging station. The properties of the proposed multicriteria shortest path problem are mathematically proved. The simulation results on randomly-generated networks show that cyclic paths are very rare, and that the generalized cost of travel is a monotone increasing function of minimum reliability threshold.

Suggested Citation

  • Ehsan Jafari & Stephen D. Boyles, 2017. "Multicriteria Stochastic Shortest Path Problem for Electric Vehicles," Networks and Spatial Economics, Springer, vol. 17(3), pages 1043-1070, September.
    • Handle: RePEc:kap:netspa:v:17:y:2017:i:3:d:10.1007_s11067-017-9358-x
    DOI: 10.1007/s11067-017-9358-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11067-017-9358-x
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11067-017-9358-x?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. Carraway, Robert L. & Morin, Thomas L. & Moskowitz, Herbert, 1990. "Generalized dynamic programming for multicriteria optimization," European Journal of Operational Research, Elsevier, vol. 44(1), pages 95-104, January.
    2. Yongxi Huang & Shengyin Li & Zhen Qian, 2015. "Optimal Deployment of Alternative Fueling Stations on Transportation Networks Considering Deviation Paths," Networks and Spatial Economics, Springer, vol. 15(1), pages 183-204, March.
    3. Bi Chen & William Lam & Agachai Sumalee & Qingquan Li & Hu Shao & Zhixiang Fang, 2013. "Finding Reliable Shortest Paths in Road Networks Under Uncertainty," Networks and Spatial Economics, Springer, vol. 13(2), pages 123-148, June.
    4. 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.
    5. Miller-Hooks, Elise & Mahmassani, Hani, 2003. "Path comparisons for a priori and time-adaptive decisions in stochastic, time-varying networks," European Journal of Operational Research, Elsevier, vol. 146(1), pages 67-82, April.
    6. Yu Marco Nie & Xing Wu, 2009. "Reliable a Priori Shortest Path Problem with Limited Spatial and Temporal Dependencies," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 169-195, Springer.
    7. Elise D. Miller-Hooks & Hani S. Mahmassani, 2000. "Least Expected Time Paths in Stochastic, Time-Varying Transportation Networks," Transportation Science, INFORMS, vol. 34(2), pages 198-215, May.
    8. 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).
    9. Pretolani, Daniele, 2000. "A directed hypergraph model for random time dependent shortest paths," European Journal of Operational Research, Elsevier, vol. 123(2), pages 315-324, June.
    10. Matthias Müller-Hannemann & Karsten Weihe, 2006. "On the cardinality of the Pareto set in bicriteria shortest path problems," Annals of Operations Research, Springer, vol. 147(1), pages 269-286, October.
    11. Stephen Boyles & S. Waller, 2011. "Optimal Information Location for Adaptive Routing," Networks and Spatial Economics, Springer, vol. 11(2), pages 233-254, June.
    12. Nie, Yu (Marco) & Ghamami, Mehrnaz, 2013. "A corridor-centric approach to planning electric vehicle charging infrastructure," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 172-190.
    13. Adler, Jonathan D. & Mirchandani, Pitu B., 2014. "Online routing and battery reservations for electric vehicles with swappable batteries," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 285-302.
    14. Nie, Yu (Marco) & Wu, Xing, 2009. "Shortest path problem considering on-time arrival probability," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 597-613, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marianne Guillet & Maximilian Schiffer, 2023. "Coordinated charging station search in stochastic environments: A multiagent approach," Production and Operations Management, Production and Operations Management Society, vol. 32(8), pages 2596-2618, August.
    2. Bektaş, Tolga & Ehmke, Jan Fabian & Psaraftis, Harilaos N. & Puchinger, Jakob, 2019. "The role of operational research in green freight transportation," European Journal of Operational Research, Elsevier, vol. 274(3), pages 807-823.
    3. Haluk Yapicioglu, 2018. "Multiperiod Multi Traveling Salesmen Problem Considering Time Window Constraints with an Application to a Real World Case," Networks and Spatial Economics, Springer, vol. 18(4), pages 773-801, December.
    4. Jie Ma & Lin Cheng & Dawei Li & Qiang Tu, 2018. "Stochastic Electric Vehicle Network Considering Environmental Costs," Sustainability, MDPI, vol. 10(8), pages 1-16, August.
    5. Xiang Zhang & David Rey & S. Travis Waller & Nathan Chen, 2019. "Range-Constrained Traffic Assignment with Multi-Modal Recharge for Electric Vehicles," Networks and Spatial Economics, Springer, vol. 19(2), pages 633-668, June.
    6. Qiang Tu & Lin Cheng & Dawei Li & Jie Ma & Chao Sun, 2018. "Stochastic Transportation Network Considering ATIS with the Information of Environmental Cost," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    7. Kai Liu & Sijia Luo & Jing Zhou, 2020. "En-Route Battery Management and a Mixed Network Equilibrium Problem Based on Electric Vehicle Drivers’ En-Route Recharging Behaviors," Energies, MDPI, vol. 13(16), pages 1-14, August.
    8. Yongxing Wang & Jun Bi & Chaoru Lu & Cong Ding, 2020. "Route Guidance Strategies for Electric Vehicles by Considering Stochastic Charging Demands in a Time-Varying Road Network," Energies, MDPI, vol. 13(9), pages 1-24, May.
    9. Zhiwei Chen & Yucong Hu & Jutint Li & Xing Wu, 2020. "Optimal Deployment of Electric Bicycle Sharing Stations: Model Formulation and Solution Technique," Networks and Spatial Economics, Springer, vol. 20(1), pages 99-136, March.

    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. Shen, Zuo-Jun Max & Feng, Bo & Mao, Chao & Ran, Lun, 2019. "Optimization models for electric vehicle service operations: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 462-477.
    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. A. Arun Prakash & Karthik K. Srinivasan, 2017. "Finding the Most Reliable Strategy on Stochastic and Time-Dependent Transportation Networks: A Hypergraph Based Formulation," Networks and Spatial Economics, Springer, vol. 17(3), pages 809-840, September.
    4. Cen, Xuekai & Lo, Hong K. & Li, Lu & Lee, Enoch, 2018. "Modeling electric vehicles adoption for urban commute trips," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 431-454.
    5. Shaohua Cui & Hui Zhao & Cuiping Zhang, 2018. "Multiple Types of Plug-In Charging Facilities’ Location-Routing Problem with Time Windows for Mobile Charging Vehicles," Sustainability, MDPI, vol. 10(8), pages 1-26, August.
    6. Yang, Lixing & Zhou, Xuesong, 2017. "Optimizing on-time arrival probability and percentile travel time for elementary path finding in time-dependent transportation networks: Linear mixed integer programming reformulations," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 68-91.
    7. Xu, Min & Meng, Qiang & Liu, Kai, 2017. "Network user equilibrium problems for the mixed battery electric vehicles and gasoline vehicles subject to battery swapping stations and road grade constraints," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 138-166.
    8. Hof, Julian & Schneider, Michael & Goeke, Dominik, 2017. "Solving the battery swap station location-routing problem with capacitated electric vehicles using an AVNS algorithm for vehicle-routing problems with intermediate stops," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 102-112.
    9. Yang, Lixing & Zhou, Xuesong, 2014. "Constraint reformulation and a Lagrangian relaxation-based solution algorithm for a least expected time path problem," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 22-44.
    10. Huang, He & Gao, Song, 2012. "Optimal paths in dynamic networks with dependent random link travel times," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 579-598.
    11. Goeke, Dominik & Schneider, Michael, 2015. "Routing a mixed fleet of electric and conventional vehicles," European Journal of Operational Research, Elsevier, vol. 245(1), pages 81-99.
    12. He Huang & Song Gao, 2018. "Trajectory-Adaptive Routing in Dynamic Networks with Dependent Random Link Travel Times," Transportation Science, INFORMS, vol. 52(1), pages 102-117, January.
    13. Michael Redmond & Ann Melissa Campbell & Jan Fabian Ehmke, 2020. "Data-driven planning of reliable itineraries in multi-modal transit networks," Public Transport, Springer, vol. 12(1), pages 171-205, March.
    14. Jie, Wanchen & Yang, Jun & Zhang, Min & Huang, Yongxi, 2019. "The two-echelon capacitated electric vehicle routing problem with battery swapping stations: Formulation and efficient methodology," European Journal of Operational Research, Elsevier, vol. 272(3), pages 879-904.
    15. Liu, Yong & Xiao, Feng & Shen, Minyu & Zhao, Lin & Li, Lu, 2024. "The k-th order mean-deviation model for route choice under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).
    16. Wen, Liang & Çatay, Bülent & Eglese, Richard, 2014. "Finding a minimum cost path between a pair of nodes in a time-varying road network with a congestion charge," European Journal of Operational Research, Elsevier, vol. 236(3), pages 915-923.
    17. Goeke, D. & Schneider, M., 2015. "Routing a Mixed Fleet of Electric and Conventional Vehicles," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65939, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    18. Nielsen, Lars Relund & Pretolani, Daniele & Andersen, Kim Allan, 2004. "K shortest paths in stochastic time-dependent networks," CORAL Working Papers L-2004-05, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    19. Brandstätter, Georg & Kahr, Michael & Leitner, Markus, 2017. "Determining optimal locations for charging stations of electric car-sharing systems under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 17-35.
    20. Chen, Bi Yu & Li, Qingquan & Lam, William H.K., 2016. "Finding the k reliable shortest paths under travel time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 189-203.

    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:kap:netspa:v:17:y:2017:i:3:d:10.1007_s11067-017-9358-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.