IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v81y2018icp208-219.html
   My bibliography  Save this article

A practical time slot management and routing problem for attended home services

Author

Listed:
  • Bruck, Bruno P.
  • Cordeau, Jean-François
  • Iori, Manuel

Abstract

This paper describes the solution methodology developed to address an attended home delivery problem faced by an Italian provider of gas, electricity, and water services. This company operates in several regions and must dispatch technicians to customer locations where they carry out installation or maintenance activities within time intervals chosen by the customers. The problem consists of creating time slot tables specifying the amount of resources allocated to each region in each time slot, and of routing technicians in a cost-effective way. We propose a large neighborhood search (LNS) heuristic to create time slot tables by relying on various simulation strategies to represent the behavior of customers and on an integer linear program to optimize the routing of technicians. In addition, we also use a second integer program as a repair mechanism inside the LNS heuristic. Computational experiments carried out on data provided by the company confirm the efficiency of the proposed methodology.

Suggested Citation

  • Bruck, Bruno P. & Cordeau, Jean-François & Iori, Manuel, 2018. "A practical time slot management and routing problem for attended home services," Omega, Elsevier, vol. 81(C), pages 208-219.
    • Handle: RePEc:eee:jomega:v:81:y:2018:i:c:p:208-219
    DOI: 10.1016/j.omega.2017.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048317300609
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2017.11.003?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. Liu, Ran & Xie, Xiaolan & Garaix, Thierry, 2014. "Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics," Omega, Elsevier, vol. 47(C), pages 17-32.
    2. Ann Melissa Campbell & Martin W. P. Savelsbergh, 2005. "Decision Support for Consumer Direct Grocery Initiatives," Transportation Science, INFORMS, vol. 39(3), pages 313-327, August.
    3. Xinan Yang & Arne K. Strauss & Christine S. M. Currie & Richard Eglese, 2016. "Choice-Based Demand Management and Vehicle Routing in E-Fulfillment," Transportation Science, INFORMS, vol. 50(2), pages 473-488, May.
    4. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms," Transportation Science, INFORMS, vol. 39(1), pages 104-118, February.
    5. Ann Melissa Campbell & Martin Savelsbergh, 2006. "Incentive Schemes for Attended Home Delivery Services," Transportation Science, INFORMS, vol. 40(3), pages 327-341, August.
    6. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    7. Chris Groër & Bruce Golden & Edward Wasil, 2009. "The Consistent Vehicle Routing Problem," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 630-643, February.
    8. Bektas, Tolga, 2006. "The multiple traveling salesman problem: an overview of formulations and solution procedures," Omega, Elsevier, vol. 34(3), pages 209-219, June.
    9. Remy Spliet & Adriana F. Gabor, 2015. "The Time Window Assignment Vehicle Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 721-731, November.
    10. Niels Agatz & Ann Campbell & Moritz Fleischmann & Martin Savelsbergh, 2011. "Time Slot Management in Attended Home Delivery," Transportation Science, INFORMS, vol. 45(3), pages 435-449, August.
    11. David Pisinger & Stefan Ropke, 2010. "Large Neighborhood Search," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 399-419, Springer.
    12. Catherine Cleophas & Jan Ehmke, 2014. "When Are Deliveries Profitable?," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(3), pages 153-163, June.
    13. Kara, Imdat & Bektas, Tolga, 2006. "Integer linear programming formulations of multiple salesman problems and its variations," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1449-1458, November.
    14. Desaulniers, Guy & Lavigne, June & Soumis, Francois, 1998. "Multi-depot vehicle scheduling problems with time windows and waiting costs," European Journal of Operational Research, Elsevier, vol. 111(3), pages 479-494, December.
    15. Spliet, Remy & Desaulniers, Guy, 2015. "The discrete time window assignment vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 244(2), pages 379-391.
    16. Chen, Xi & Thomas, Barrett W. & Hewitt, Mike, 2016. "The technician routing problem with experience-based service times," Omega, Elsevier, vol. 61(C), pages 49-61.
    17. Baldacci, Roberto & Mingozzi, Aristide & Roberti, Roberto, 2012. "Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints," European Journal of Operational Research, Elsevier, vol. 218(1), pages 1-6.
    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. Subramanyam, Anirudh & Wang, Akang & Gounaris, Chrysanthos E., 2018. "A scenario decomposition algorithm for strategic time window assignment vehicle routing problems," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 296-317.
    2. Soriano, Adria & Vidal, Thibaut & Gansterer, Margaretha & Doerner, Karl, 2020. "The vehicle routing problem with arrival time diversification on a multigraph," European Journal of Operational Research, Elsevier, vol. 286(2), pages 564-575.
    3. María I. Restrepo & Frédéric Semet & Thomas Pocreau, 2019. "Integrated Shift Scheduling and Load Assignment Optimization for Attended Home Delivery," Transportation Science, INFORMS, vol. 53(4), pages 1150-1174, July.
    4. Waßmuth, Katrin & Köhler, Charlotte & Agatz, Niels & Fleischmann, Moritz, 2023. "Demand management for attended home delivery—A literature review," European Journal of Operational Research, Elsevier, vol. 311(3), pages 801-815.
    5. Mancini, Simona & Gansterer, Margaretha & Triki, Chefi, 2023. "Locker box location planning under uncertainty in demand and capacity availability," Omega, Elsevier, vol. 120(C).
    6. Visser, T.R. & Savelsbergh, M.W.P., 2019. "Strategic Time Slot Management: A Priori Routing for Online Grocery Retailing," Econometric Institute Research Papers EI2019-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. 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.
    8. Lang, Magdalena A.K. & Cleophas, Catherine & Ehmke, Jan Fabian, 2021. "Multi-criteria decision making in dynamic slotting for attended home deliveries," Omega, Elsevier, vol. 102(C).
    9. Koch, Sebastian & Klein, Robert, 2020. "Route-based approximate dynamic programming for dynamic pricing in attended home delivery," European Journal of Operational Research, Elsevier, vol. 287(2), pages 633-652.
    10. Naderi, Bahman & Begen, Mehmet A. & Zaric, Gregory S. & Roshanaei, Vahid, 2023. "A novel and efficient exact technique for integrated staffing, assignment, routing, and scheduling of home care services under uncertainty," Omega, Elsevier, vol. 116(C).
    11. Fleckenstein, David & Klein, Robert & Steinhardt, Claudius, 2023. "Recent advances in integrating demand management and vehicle routing: A methodological review," European Journal of Operational Research, Elsevier, vol. 306(2), pages 499-518.
    12. Bruno P. Bruck & Filippo Castegini & Jean-François Cordeau & Manuel Iori & Tommaso Poncemi & Dario Vezzali, 2020. "A Decision Support System for Attended Home Services," Interfaces, INFORMS, vol. 50(2), pages 137-152, March.
    13. Sharif Azadeh, Sh. & Atasoy, Bilge & Ben-Akiva, Moshe E. & Bierlaire, M. & Maknoon, M.Y., 2022. "Choice-driven dial-a-ride problem for demand responsive mobility service," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 128-149.

    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. Koch, Sebastian & Klein, Robert, 2020. "Route-based approximate dynamic programming for dynamic pricing in attended home delivery," European Journal of Operational Research, Elsevier, vol. 287(2), pages 633-652.
    2. Waßmuth, Katrin & Köhler, Charlotte & Agatz, Niels & Fleischmann, Moritz, 2023. "Demand management for attended home delivery—A literature review," European Journal of Operational Research, Elsevier, vol. 311(3), pages 801-815.
    3. Visser, T.R. & Savelsbergh, M.W.P., 2019. "Strategic Time Slot Management: A Priori Routing for Online Grocery Retailing," Econometric Institute Research Papers EI2019-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Subramanyam, Anirudh & Wang, Akang & Gounaris, Chrysanthos E., 2018. "A scenario decomposition algorithm for strategic time window assignment vehicle routing problems," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 296-317.
    5. Ehmke, Jan Fabian & Campbell, Ann Melissa, 2014. "Customer acceptance mechanisms for home deliveries in metropolitan areas," European Journal of Operational Research, Elsevier, vol. 233(1), pages 193-207.
    6. Robert Klein & Michael Neugebauer & Dimitri Ratkovitch & Claudius Steinhardt, 2019. "Differentiated Time Slot Pricing Under Routing Considerations in Attended Home Delivery," Service Science, INFORMS, vol. 53(1), pages 236-255, February.
    7. Strauss, Arne & Gülpınar, Nalan & Zheng, Yijun, 2021. "Dynamic pricing of flexible time slots for attended home delivery," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1022-1041.
    8. Fleckenstein, David & Klein, Robert & Steinhardt, Claudius, 2023. "Recent advances in integrating demand management and vehicle routing: A methodological review," European Journal of Operational Research, Elsevier, vol. 306(2), pages 499-518.
    9. Mohamed Cissé & Semih Yalçindag & Yannick Kergosien & Evren Sahin & Christophe Lenté & Andrea Matta, 2017. "OR problems related to Home Health Care: A review of relevant routing and scheduling problems," Post-Print hal-01736714, HAL.
    10. Yan Cheng Hsu & Jose L. Walteros & Rajan Batta, 2020. "Solving the petroleum replenishment and routing problem with variable demands and time windows," Annals of Operations Research, Springer, vol. 294(1), pages 9-46, November.
    11. van der Hagen, L. & Agatz, N.A.H. & Spliet, R. & Visser, T.R. & Kok, A.L., 2022. "Machine Learning-Based Feasibility Checks for Dynamic Time Slot Management," ERIM Report Series Research in Management ERS-2022-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    12. Magdalena A. K. Lang & Catherine Cleophas & Jan Fabian Ehmke, 2021. "Anticipative Dynamic Slotting for Attended Home Deliveries," SN Operations Research Forum, Springer, vol. 2(4), pages 1-39, December.
    13. Yang, Xinan & Strauss, Arne K., 2017. "An approximate dynamic programming approach to attended home delivery management," European Journal of Operational Research, Elsevier, vol. 263(3), pages 935-945.
    14. Han, Shuihua & Zhao, Ling & Chen, Kui & Luo, Zong-wei & Mishra, Deepa, 2017. "Appointment scheduling and routing optimization of attended home delivery system with random customer behavior," European Journal of Operational Research, Elsevier, vol. 262(3), pages 966-980.
    15. Bruno P. Bruck & Filippo Castegini & Jean-François Cordeau & Manuel Iori & Tommaso Poncemi & Dario Vezzali, 2020. "A Decision Support System for Attended Home Services," Interfaces, INFORMS, vol. 50(2), pages 137-152, March.
    16. Spliet, Remy & Desaulniers, Guy, 2015. "The discrete time window assignment vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 244(2), pages 379-391.
    17. Avraham, Edison & Raviv, Tal, 2021. "The steady-state mobile personnel booking problem," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 266-288.
    18. Robert Klein & Jochen Mackert & Michael Neugebauer & Claudius Steinhardt, 2018. "A model-based approximation of opportunity cost for dynamic pricing in attended home delivery," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 969-996, October.
    19. Nils Boysen & Stefan Fedtke & Stefan Schwerdfeger, 2021. "Last-mile delivery concepts: a survey from an operational research perspective," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 1-58, March.
    20. Neves-Moreira, Fábio & Pereira da Silva, Diogo & Guimarães, Luís & Amorim, Pedro & Almada-Lobo, Bernardo, 2018. "The time window assignment vehicle routing problem with product dependent deliveries," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 163-183.

    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:jomega:v:81:y:2018:i:c:p:208-219. 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/375/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.