IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i18p2822-d1476220.html
   My bibliography  Save this article

A Novel Tourist Trip Design Problem with Stochastic Travel Times and Partial Charging for Battery Electric Vehicles

Author

Listed:
  • Samita Kedkaew

    (Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Warisa Nakkiew

    (Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Parida Jewpanya

    (Department of Industrial Engineering, Rajamangala University of Technology Lanna, Tak 63000, Thailand)

  • Wasawat Nakkiew

    (Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

This study proposes a novel mathematical model for the Multi-Day Tourist Trip Design Problem with Stochastic Travel Time and Partial Charging for Battery Electric Vehicle (MD-TTDP-STT-PCBEV). To the best of our knowledge, no prior study has fully incorporated the use of BEVs into TTDP models. Given the limited driving range of BEVs, the model requires decisions regarding the locations and policy for recharging the vehicle’s battery. The problem also incorporates real-world uncertainty by considering travel time as a random variable subjected to normal distribution. The model is formulated using chance-constraint programming, aiming to find optimal tourist routes for BEVs that maximize tourist satisfaction. Numerical experiments were conducted to compare solutions between stochastic and deterministic environments. Computational experiments using the LINGO optimization solver demonstrated that the total rating scores obtained from the stochastic model with chance-constraint programming were generally lower than those from the deterministic model due to travel time uncertainties. These results highlight the importance of incorporating real-world uncertainty and variability to achieve more accurate and reliable planning.

Suggested Citation

  • Samita Kedkaew & Warisa Nakkiew & Parida Jewpanya & Wasawat Nakkiew, 2024. "A Novel Tourist Trip Design Problem with Stochastic Travel Times and Partial Charging for Battery Electric Vehicles," Mathematics, MDPI, vol. 12(18), pages 1-19, September.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:18:p:2822-:d:1476220
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/18/2822/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/18/2822/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chao, I-Ming & Golden, Bruce L. & Wasil, Edward A., 1996. "A fast and effective heuristic for the orienteering problem," European Journal of Operational Research, Elsevier, vol. 88(3), pages 475-489, February.
    2. Zheng, Weimin & Huang, Xiaoting & Li, Yuan, 2017. "Understanding the tourist mobility using GPS: Where is the next place?," Tourism Management, Elsevier, vol. 59(C), pages 267-280.
    3. Ann Campbell & Michel Gendreau & Barrett Thomas, 2011. "The orienteering problem with stochastic travel and service times," Annals of Operations Research, Springer, vol. 186(1), pages 61-81, June.
    4. Vansteenwegen, Pieter & Souffriau, Wouter & Oudheusden, Dirk Van, 2011. "The orienteering problem: A survey," European Journal of Operational Research, Elsevier, vol. 209(1), pages 1-10, February.
    5. Verbeeck, C. & Vansteenwegen, P. & Aghezzaf, E.-H., 2016. "Solving the stochastic time-dependent orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 255(3), pages 699-718.
    6. Jorge E. Mendoza & Louis-Martin Rousseau & Juan G. Villegas, 2016. "A hybrid metaheuristic for the vehicle routing problem with stochastic demand and duration constraints," Journal of Heuristics, Springer, vol. 22(4), pages 539-566, August.
    7. Chao, I-Ming & Golden, Bruce L. & Wasil, Edward A., 1996. "The team orienteering problem," European Journal of Operational Research, Elsevier, vol. 88(3), pages 464-474, February.
    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. Ruiz-Meza, José & Montoya-Torres, Jairo R., 2022. "A systematic literature review for the tourist trip design problem: Extensions, solution techniques and future research lines," Operations Research Perspectives, Elsevier, vol. 9(C).
    2. Shiri, Davood & Akbari, Vahid & Hassanzadeh, Ali, 2024. "The Capacitated Team Orienteering Problem: An online optimization framework with predictions of unknown accuracy," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
    3. Gunawan, Aldy & Lau, Hoong Chuin & Vansteenwegen, Pieter, 2016. "Orienteering Problem: A survey of recent variants, solution approaches and applications," European Journal of Operational Research, Elsevier, vol. 255(2), pages 315-332.
    4. Wu, Qinghua & He, Mu & Hao, Jin-Kao & Lu, Yongliang, 2024. "An effective hybrid evolutionary algorithm for the clustered orienteering problem," European Journal of Operational Research, Elsevier, vol. 313(2), pages 418-434.
    5. Bian, Zheyong & Liu, Xiang, 2018. "A real-time adjustment strategy for the operational level stochastic orienteering problem: A simulation-aided optimization approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 246-266.
    6. Dang, Duc-Cuong & Guibadj, Rym Nesrine & Moukrim, Aziz, 2013. "An effective PSO-inspired algorithm for the team orienteering problem," European Journal of Operational Research, Elsevier, vol. 229(2), pages 332-344.
    7. Divsalar, A. & Vansteenwegen, P. & Cattrysse, D., 2013. "A variable neighborhood search method for the orienteering problem with hotel selection," International Journal of Production Economics, Elsevier, vol. 145(1), pages 150-160.
    8. Krzysztof Ostrowski & Joanna Karbowska-Chilinska & Jolanta Koszelew & Pawel Zabielski, 2017. "Evolution-inspired local improvement algorithm solving orienteering problem," Annals of Operations Research, Springer, vol. 253(1), pages 519-543, June.
    9. Lei, Chao & Lin, Wei-Hua & Miao, Lixin, 2014. "A multicut L-shaped based algorithm to solve a stochastic programming model for the mobile facility routing and scheduling problem," European Journal of Operational Research, Elsevier, vol. 238(3), pages 699-710.
    10. Verbeeck, C. & Vansteenwegen, P. & Aghezzaf, E.-H., 2016. "Solving the stochastic time-dependent orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 255(3), pages 699-718.
    11. Balcik, Burcu, 2017. "Site selection and vehicle routing for post-disaster rapid needs assessment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 30-58.
    12. Gambardella, L.M. & Montemanni, R. & Weyland, D., 2012. "Coupling ant colony systems with strong local searches," European Journal of Operational Research, Elsevier, vol. 220(3), pages 831-843.
    13. Zhao, Yanlu & Alfandari, Laurent, 2020. "Design of diversified package tours for the digital travel industry : A branch-cut-and-price approach," European Journal of Operational Research, Elsevier, vol. 285(3), pages 825-843.
    14. He, Mu & Wu, Qinghua & Benlic, Una & Lu, Yongliang & Chen, Yuning, 2024. "An effective multi-level memetic search with neighborhood reduction for the clustered team orienteering problem," European Journal of Operational Research, Elsevier, vol. 318(3), pages 778-801.
    15. Kim, Hyunjoon & Kim, Byung-In, 2022. "Hybrid dynamic programming with bounding algorithm for the multi-profit orienteering problem," European Journal of Operational Research, Elsevier, vol. 303(2), pages 550-566.
    16. Hu, Qian & Lim, Andrew, 2014. "An iterative three-component heuristic for the team orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 232(2), pages 276-286.
    17. Zhang, Shu & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2020. "Multi-period orienteering with uncertain adoption likelihood and waiting at customers," European Journal of Operational Research, Elsevier, vol. 282(1), pages 288-303.
    18. Qinxiao Yu & Chun Cheng & Ning Zhu, 2022. "Robust Team Orienteering Problem with Decreasing Profits," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3215-3233, November.
    19. Yu, Qinxiao & Fang, Kan & Zhu, Ning & Ma, Shoufeng, 2019. "A matheuristic approach to the orienteering problem with service time dependent profits," European Journal of Operational Research, Elsevier, vol. 273(2), pages 488-503.
    20. Labadie, Nacima & Mansini, Renata & Melechovský, Jan & Wolfler Calvo, Roberto, 2012. "The Team Orienteering Problem with Time Windows: An LP-based Granular Variable Neighborhood Search," European Journal of Operational Research, Elsevier, vol. 220(1), pages 15-27.

    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:gam:jmathe:v:12:y:2024:i:18:p:2822-:d:1476220. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.