IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v309y2023i1p82-101.html
   My bibliography  Save this article

Territorial design for customers with demand frequency

Author

Listed:
  • Zhen, Lu
  • Gao, Jiajing
  • Tan, Zheyi
  • Laporte, Gilbert
  • Baldacci, Roberto

Abstract

Territorial design is an important long-term decision for urban delivery service companies, in contexts where customers are partitioned into districts. This study focuses on a territorial design problem given the demand frequency of each customer, i.e., the estimated percentage of days with demand, over the planning horizon. This study formulates a set partitioning model and designs a column generation based algorithm to solve the problem. The algorithm decomposes the original problem into a restricted master problem (RMP) and a series of pricing problems (PPs), each limited to one district. A dynamic programming based method is designed to solve the PPs efficiently. To further accelerate the solution processes of the PPs and of the RMP, some tailored strategies are also embedded within the algorithm. Numerical experiments are conducted to validate the contributions of the dynamic programming and of the acceleration strategies. Some tests based on real-world cases are also performed in order to derive some managerial insights to support the practitioners’ decisions on service territory design.

Suggested Citation

  • Zhen, Lu & Gao, Jiajing & Tan, Zheyi & Laporte, Gilbert & Baldacci, Roberto, 2023. "Territorial design for customers with demand frequency," European Journal of Operational Research, Elsevier, vol. 309(1), pages 82-101.
  • Handle: RePEc:eee:ejores:v:309:y:2023:i:1:p:82-101
    DOI: 10.1016/j.ejor.2023.01.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221723000164
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2023.01.016?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. Yanfeng Ouyang & Carlos F. Daganzo, 2006. "Discretization and Validation of the Continuum Approximation Scheme for Terminal System Design," Transportation Science, INFORMS, vol. 40(1), pages 89-98, February.
    2. Václavík, Roman & Novák, Antonín & Šůcha, Přemysl & Hanzálek, Zdeněk, 2018. "Accelerating the Branch-and-Price Algorithm Using Machine Learning," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1055-1069.
    3. Ilgaz Sungur & Yingtao Ren & Fernando Ordóñez & Maged Dessouky & Hongsheng Zhong, 2010. "A Model and Algorithm for the Courier Delivery Problem with Uncertainty," Transportation Science, INFORMS, vol. 44(2), pages 193-205, May.
    4. Mancini, Simona & Gansterer, Margaretha & Hartl, Richard F., 2021. "The collaborative consistent vehicle routing problem with workload balance," European Journal of Operational Research, Elsevier, vol. 293(3), pages 955-965.
    5. Haugland, Dag & Ho, Sin C. & Laporte, Gilbert, 2007. "Designing delivery districts for the vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 180(3), pages 997-1010, August.
    6. John Gunnar Carlsson, 2012. "Dividing a Territory Among Several Vehicles," INFORMS Journal on Computing, INFORMS, vol. 24(4), pages 565-577, November.
    7. Francis, Peter & Smilowitz, Karen, 2006. "Modeling techniques for periodic vehicle routing problems," Transportation Research Part B: Methodological, Elsevier, vol. 40(10), pages 872-884, December.
    8. Rodríguez-Martín, Inmaculada & Salazar-González, Juan-José & Yaman, Hande, 2019. "The periodic vehicle routing problem with driver consistency," European Journal of Operational Research, Elsevier, vol. 273(2), pages 575-584.
    9. Lu Zhen & Wenya Lv & Kai Wang & Chengle Ma & Ziheng Xu, 2020. "Consistent vehicle routing problem with simultaneous distribution and collection," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(5), pages 813-830, May.
    10. Luo, Zhixing & Qin, Hu & Che, ChanHou & Lim, Andrew, 2015. "On service consistency in multi-period vehicle routing," European Journal of Operational Research, Elsevier, vol. 243(3), pages 731-744.
    11. Mladenovic, Nenad & Brimberg, Jack & Hansen, Pierre & Moreno-Perez, Jose A., 2007. "The p-median problem: A survey of metaheuristic approaches," European Journal of Operational Research, Elsevier, vol. 179(3), pages 927-939, June.
    12. John Gunnar Carlsson & Erick Delage, 2013. "Robust Partitioning for Stochastic Multivehicle Routing," Operations Research, INFORMS, vol. 61(3), pages 727-744, June.
    13. Attila A. Kovacs & Bruce L. Golden & Richard F. Hartl & Sophie N. Parragh, 2015. "The Generalized Consistent Vehicle Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 796-816, November.
    14. Cortés, Cristián E. & Gendreau, Michel & Rousseau, Louis Martin & Souyris, Sebastián & Weintraub, Andrés, 2014. "Branch-and-price and constraint programming for solving a real-life technician dispatching problem," European Journal of Operational Research, Elsevier, vol. 238(1), pages 300-312.
    15. Chris Groër & Bruce Golden & Edward Wasil, 2009. "The Consistent Vehicle Routing Problem," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 630-643, February.
    16. Sandoval, M. Gabriela & Álvarez-Miranda, Eduardo & Pereira, Jordi & Ríos-Mercado, Roger Z. & Díaz, Juan A., 2022. "A novel districting design approach for on-time last-mile delivery: An application on an express postal company," Omega, Elsevier, vol. 113(C).
    17. Karen Smilowitz & Maciek Nowak & Tingting Jiang, 2013. "Workforce Management in Periodic Delivery Operations," Transportation Science, INFORMS, vol. 47(2), pages 214-230, May.
    18. Peter Francis & Karen Smilowitz & Michal Tzur, 2006. "The Period Vehicle Routing Problem with Service Choice," Transportation Science, INFORMS, vol. 40(4), pages 439-454, November.
    19. Lu Zhen & Jiajing Gao & Zheyi Tan & Shuaian Wang & Roberto Baldacci, 2023. "Branch-price-and-cut for trucks and drones cooperative delivery," IISE Transactions, Taylor & Francis Journals, vol. 55(3), pages 271-287, March.
    20. Bard, Jonathan F. & Jarrah, Ahmad I., 2009. "Large-scale constrained clustering for rationalizing pickup and delivery operations," Transportation Research Part B: Methodological, Elsevier, vol. 43(5), pages 542-561, June.
    21. Bender, Matthias & Meyer, Anne & Kalcsics, Jörg & Nickel, Stefan, 2016. "The multi-period service territory design problem – An introduction, a model and a heuristic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 135-157.
    22. Anuj Mehrotra & Ellis L. Johnson & George L. Nemhauser, 1998. "An Optimization Based Heuristic for Political Districting," Management Science, INFORMS, vol. 44(8), pages 1100-1114, August.
    23. Zhou, Lin & Zhen, Lu & Baldacci, Roberto & Boschetti, Marco & Dai, Ying & Lim, Andrew, 2021. "A Heuristic Algorithm for solving a large-scale real-world territory design problem," Omega, Elsevier, vol. 103(C).
    24. Sourour Elloumi & Martine Labbé & Yves Pochet, 2004. "A New Formulation and Resolution Method for the p-Center Problem," INFORMS Journal on Computing, INFORMS, vol. 16(1), pages 84-94, February.
    25. Nikzad, Erfaneh & Bashiri, Mahdi & Abbasi, Babak, 2021. "A matheuristic algorithm for stochastic home health care planning," European Journal of Operational Research, Elsevier, vol. 288(3), pages 753-774.
    26. Matthias Bender & Jörg Kalcsics, 2020. "Multi-Period Service Territory Design," International Series in Operations Research & Management Science, in: Roger Z. Ríos-Mercado (ed.), Optimal Districting and Territory Design, chapter 0, pages 129-152, Springer.
    27. Bender, Matthias & Kalcsics, Jörg & Meyer, Anne, 2020. "Districting for parcel delivery services – A two-Stage solution approach and a real-World case study," Omega, Elsevier, vol. 96(C).
    28. Alexandre M. Florio & Richard F. Hartl & Stefan Minner & Juan-José Salazar-González, 2021. "A Branch-and-Price Algorithm for the Vehicle Routing Problem with Stochastic Demands and Probabilistic Duration Constraints," Transportation Science, INFORMS, vol. 55(1), pages 122-138, 1-2.
    29. Bender, Matthias & Kalcsics, Jörg & Nickel, Stefan & Pouls, Martin, 2018. "A branch-and-price algorithm for the scheduling of customer visits in the context of multi-period service territory design," European Journal of Operational Research, Elsevier, vol. 269(1), pages 382-396.
    30. Carlos F. Daganzo, 1984. "The Distance Traveled to Visit N Points with a Maximum of C Stops per Vehicle: An Analytic Model and an Application," Transportation Science, INFORMS, vol. 18(4), pages 331-350, November.
    31. Hongsheng Zhong & Randolph W. Hall & Maged Dessouky, 2007. "Territory Planning and Vehicle Dispatching with Driver Learning," Transportation Science, INFORMS, vol. 41(1), pages 74-89, February.
    32. Jörg Kalcsics & Stefan Nickel & Michael Schröder, 2005. "Towards a unified territorial design approach — Applications, algorithms and GIS integration," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 13(1), pages 1-56, June.
    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. Cristina Lopes & Ana Maria Rodrigues & Valeria Romanciuc & José Soeiro Ferreira & Elif Göksu Öztürk & Cristina Oliveira, 2023. "Divide and Conquer: A Location-Allocation Approach to Sectorization," Mathematics, MDPI, vol. 11(11), pages 1-19, June.

    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. Zhou, Lin & Zhen, Lu & Baldacci, Roberto & Boschetti, Marco & Dai, Ying & Lim, Andrew, 2021. "A Heuristic Algorithm for solving a large-scale real-world territory design problem," Omega, Elsevier, vol. 103(C).
    2. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    3. Bender, Matthias & Kalcsics, Jörg & Meyer, Anne, 2020. "Districting for parcel delivery services – A two-Stage solution approach and a real-World case study," Omega, Elsevier, vol. 96(C).
    4. Rodríguez-Martín, Inmaculada & Yaman, Hande, 2022. "Periodic Vehicle Routing Problem with Driver Consistency and service time optimization," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 468-484.
    5. Li, Yifu & Zhou, Chenhao & Yuan, Peixue & Ngo, Thi Tu Anh, 2023. "Experience-based territory planning and driver assignment with predicted demand and driver present condition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    6. Yao, Yu & Van Woensel, Tom & Veelenturf, Lucas P. & Mo, Pengli, 2021. "The consistent vehicle routing problem considering path consistency in a road network," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 21-44.
    7. Antonio Diglio & Stefan Nickel & Francisco Saldanha-da-Gama, 2020. "Towards a stochastic programming modeling framework for districting," Annals of Operations Research, Springer, vol. 292(1), pages 249-285, September.
    8. Jabali, Ola & Gendreau, Michel & Laporte, Gilbert, 2012. "A continuous approximation model for the fleet composition problem," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1591-1606.
    9. Ulmer, Marlin & Nowak, Maciek & Mattfeld, Dirk & Kaminski, Bogumił, 2020. "Binary driver-customer familiarity in service routing," European Journal of Operational Research, Elsevier, vol. 286(2), pages 477-493.
    10. Anna Franceschetti & Ola Jabali & Gilbert Laporte, 2017. "Continuous approximation models in freight distribution management," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 413-433, October.
    11. Yang, Meng & Ni, Yaodong & Song, Qinyu, 2022. "Optimizing driver consistency in the vehicle routing problem under uncertain environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    12. Jost, Christian & Jungwirth, Alexander & Kolisch, Rainer & Schiffels, Sebastian, 2022. "Consistent vehicle routing with pickup decisions - Insights from sport academy training transfers," European Journal of Operational Research, Elsevier, vol. 298(1), pages 337-350.
    13. Attila A. Kovacs & Bruce L. Golden & Richard F. Hartl & Sophie N. Parragh, 2015. "The Generalized Consistent Vehicle Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 796-816, November.
    14. Michael Schneider & Andreas Stenger & Fabian Schwahn & Daniele Vigo, 2015. "Territory-Based Vehicle Routing in the Presence of Time-Window Constraints," Transportation Science, INFORMS, vol. 49(4), pages 732-751, November.
    15. Sandoval, M. Gabriela & Álvarez-Miranda, Eduardo & Pereira, Jordi & Ríos-Mercado, Roger Z. & Díaz, Juan A., 2022. "A novel districting design approach for on-time last-mile delivery: An application on an express postal company," Omega, Elsevier, vol. 113(C).
    16. Jorge Oyola & Halvard Arntzen & David L. Woodruff, 2017. "The stochastic vehicle routing problem, a literature review, Part II: solution methods," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 349-388, December.
    17. Rodríguez-Martín, Inmaculada & Salazar-González, Juan-José & Yaman, Hande, 2019. "The periodic vehicle routing problem with driver consistency," European Journal of Operational Research, Elsevier, vol. 273(2), pages 575-584.
    18. Stavropoulou, F. & Repoussis, P.P. & Tarantilis, C.D., 2019. "The Vehicle Routing Problem with Profits and consistency constraints," European Journal of Operational Research, Elsevier, vol. 274(1), pages 340-356.
    19. Diglio, Antonio & Peiró, Juanjo & Piccolo, Carmela & Saldanha-da-Gama, Francisco, 2021. "Solutions for districting problems with chance-constrained balancing requirements," Omega, Elsevier, vol. 103(C).
    20. Huang, Yixiao & Savelsbergh, Martin & Zhao, Lei, 2018. "Designing logistics systems for home delivery in densely populated urban areas," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 95-125.

    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:ejores:v:309:y:2023:i:1:p:82-101. 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/locate/eor .

    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.