IDEAS home Printed from https://ideas.repec.org/a/spr/eurjtl/v7y2018i4d10.1007_s13676-018-0121-3.html
   My bibliography  Save this article

The opportunity cost of time window violations

Author

Listed:
  • Matteo Salani

    (USI/DTI-SUPSI)

  • Maria Battarra

    (University of Bath)

Abstract

This paper studies a variant of the vehicle routing problem with soft time windows (VRPSTW), inspired by real-world distribution problems. In applications, violations of the prescribed delivery time are commonly accepted. Customers’ inconvenience due to early or late arrival is typically modelled as a penalty cost included in the VRPSTW objective function, added to the routing costs. However, weighting routing costs against customer inconvenience is not straightforward for practitioners. In our problem definition, practitioners evaluate solutions by comparison with the hard time windows solution. The desired routing cost saving is set by the practitioners as a percentage of the nominal solution’s routing costs. The objective function minimizes the time window violations, or the customer inconvenience, with respect to the nominal solution. This allows practitioners to quantify the opportunity cost (i.e. the customer inconvenience), when a target routing cost saving is imposed. To solve the problem, we apply two exact algorithms: the first is based on a standard branch-and-cut-and-price (BCP), the second is a BCP nested in a bisection algorithm. Computational results demonstrate that the second algorithm outperforms the standard implementation. Solutions obtained with the opportunity cost interpretation of soft time windows are then compared with solutions obtained using both hard time windows and the standard interpretation of soft time windows.

Suggested Citation

  • Matteo Salani & Maria Battarra, 2018. "The opportunity cost of time window violations," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(4), pages 343-361, December.
  • Handle: RePEc:spr:eurjtl:v:7:y:2018:i:4:d:10.1007_s13676-018-0121-3
    DOI: 10.1007/s13676-018-0121-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13676-018-0121-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13676-018-0121-3?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. Thomas R. Sexton & Lawrence D. Bodin, 1985. "Optimizing Single Vehicle Many-to-Many Operations with Desired Delivery Times: I. Scheduling," Transportation Science, INFORMS, vol. 19(4), pages 378-410, November.
    2. T. Ibaraki & S. Imahori & M. Kubo & T. Masuda & T. Uno & M. Yagiura, 2005. "Effective Local Search Algorithms for Routing and Scheduling Problems with General Time-Window Constraints," Transportation Science, INFORMS, vol. 39(2), pages 206-232, May.
    3. W-C Chiang & R A Russell, 2004. "A metaheuristic for the vehicle-routeing problem with soft time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1298-1310, December.
    4. Éric Taillard & Philippe Badeau & Michel Gendreau & François Guertin & Jean-Yves Potvin, 1997. "A Tabu Search Heuristic for the Vehicle Routing Problem with Soft Time Windows," Transportation Science, INFORMS, vol. 31(2), pages 170-186, May.
    5. Qureshi, A.G. & Taniguchi, E. & Yamada, T., 2009. "An exact solution approach for vehicle routing and scheduling problems with soft time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 960-977, November.
    6. Fagerholt, Kjetil, 2001. "Ship scheduling with soft time windows: An optimisation based approach," European Journal of Operational Research, Elsevier, vol. 131(3), pages 559-571, June.
    7. Yiannis A. Koskosidis & Warren B. Powell & Marius M. Solomon, 1992. "An Optimization-Based Heuristic for Vehicle Routing and Scheduling with Soft Time Window Constraints," Transportation Science, INFORMS, vol. 26(2), pages 69-85, May.
    8. Z Fu & R Eglese & L Y O Li, 2008. "A unified tabu search algorithm for vehicle routing problems with soft time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 663-673, May.
    9. Min, Hokey, 1991. "A multiobjective vehicle routing problem with soft time windows: the case of a public library distribution system," Socio-Economic Planning Sciences, Elsevier, vol. 25(3), pages 179-188.
    10. Guy Desaulniers & Jacques Desrosiers & Yvan Dumas & Marius M. Solomon & François Soumis, 1997. "Daily Aircraft Routing and Scheduling," Management Science, INFORMS, vol. 43(6), pages 841-855, June.
    11. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    12. Ioannou, George & Kritikos, Manolis & Prastacos, Gregory, 2003. "A problem generator-solver heuristic for vehicle routing with soft time windows," Omega, Elsevier, vol. 31(1), pages 41-53, February.
    13. Yvan Dumas & François Soumis & Jacques Desrosiers, 1990. "Technical Note—Optimizing the Schedule for a Fixed Vehicle Path with Convex Inconvenience Costs," Transportation Science, INFORMS, vol. 24(2), pages 145-152, May.
    14. Bhusiri, Narath & Qureshi, Ali Gul & Taniguchi, Eiichi, 2014. "The trade-off between fixed vehicle costs and time-dependent arrival penalties in a routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 1-22.
    15. Salani, Matteo & Vacca, Ilaria, 2011. "Branch and price for the vehicle routing problem with discrete split deliveries and time windows," European Journal of Operational Research, Elsevier, vol. 213(3), pages 470-477, September.
    16. Ferland, Jacques A. & Fortin, Luc, 1989. "Vehicles scheduling with sliding time windows," European Journal of Operational Research, Elsevier, vol. 38(2), pages 213-226, January.
    17. Thomas R. Sexton & Lawrence D. Bodin, 1985. "Optimizing Single Vehicle Many-to-Many Operations with Desired Delivery Times: II. Routing," Transportation Science, INFORMS, vol. 19(4), pages 411-435, November.
    18. 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. Ramon Faganello Fachini & Vinícius Amaral Armentano & Franklina Maria Bragion Toledo, 2022. "A Granular Local Search Matheuristic for a Heterogeneous Fleet Vehicle Routing Problem with Stochastic Travel Times," Networks and Spatial Economics, Springer, vol. 22(1), pages 33-64, March.
    2. Qie He & Stefan Irnich & Yongjia Song, 2019. "Branch-and-Cut-and-Price for the Vehicle Routing Problem with Time Windows and Convex Node Costs," Transportation Science, INFORMS, vol. 53(5), pages 1409-1426, September.

    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. Hideki Hashimoto & Mutsunori Yagiura & Shinji Imahori & Toshihide Ibaraki, 2013. "Recent progress of local search in handling the time window constraints of the vehicle routing problem," Annals of Operations Research, Springer, vol. 204(1), pages 171-187, April.
    2. Bhusiri, Narath & Qureshi, Ali Gul & Taniguchi, Eiichi, 2014. "The trade-off between fixed vehicle costs and time-dependent arrival penalties in a routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 1-22.
    3. R A Russell & T L Urban, 2008. "Vehicle routing with soft time windows and Erlang travel times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1220-1228, September.
    4. Sébastien Mouthuy & Florence Massen & Yves Deville & Pascal Van Hentenryck, 2015. "A Multistage Very Large-Scale Neighborhood Search for the Vehicle Routing Problem with Soft Time Windows," Transportation Science, INFORMS, vol. 49(2), pages 223-238, May.
    5. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    6. Fagerholt, Kjetil, 2001. "Ship scheduling with soft time windows: An optimisation based approach," European Journal of Operational Research, Elsevier, vol. 131(3), pages 559-571, June.
    7. Qie He & Stefan Irnich & Yongjia Song, 2018. "Branch-Cut-and-Price for the Vehicle Routing Problem with Time Windows and Convex Node Costs," Working Papers 1804, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    8. Marielle Christiansen & Kjetil Fagerholt, 2002. "Robust ship scheduling with multiple time windows," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(6), pages 611-625, September.
    9. Qie He & Stefan Irnich & Yongjia Song, 2019. "Branch-and-Cut-and-Price for the Vehicle Routing Problem with Time Windows and Convex Node Costs," Transportation Science, INFORMS, vol. 53(5), pages 1409-1426, September.
    10. Junlong Zhang & William Lam & Bi Chen, 2013. "A Stochastic Vehicle Routing Problem with Travel Time Uncertainty: Trade-Off Between Cost and Customer Service," Networks and Spatial Economics, Springer, vol. 13(4), pages 471-496, December.
    11. Md. Anisul Islam & Yuvraj Gajpal, 2021. "Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    12. Calvete, Herminia I. & Gale, Carmen & Oliveros, Maria-Jose & Sanchez-Valverde, Belen, 2007. "A goal programming approach to vehicle routing problems with soft time windows," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1720-1733, March.
    13. Z Fu & R Eglese & L Y O Li, 2008. "A unified tabu search algorithm for vehicle routing problems with soft time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 663-673, May.
    14. K Fagerholt & G Laporte & I Norstad, 2010. "Reducing fuel emissions by optimizing speed on shipping routes," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 523-529, March.
    15. Schyns, M., 2015. "An ant colony system for responsive dynamic vehicle routing," European Journal of Operational Research, Elsevier, vol. 245(3), pages 704-718.
    16. Daniel Schubert & André Scholz & Gerhard Wäscher, 2018. "Integrated order picking and vehicle routing with due dates," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 1109-1139, October.
    17. Benjamin C. Shelbourne & Maria Battarra & Chris N. Potts, 2017. "The Vehicle Routing Problem with Release and Due Dates," INFORMS Journal on Computing, INFORMS, vol. 29(4), pages 705-723, November.
    18. P. Kabcome & T. Mouktonglang, 2015. "Vehicle Routing Problem for Multiple Product Types, Compartments, and Trips with Soft Time Windows," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2015, pages 1-9, July.
    19. Aderemi Oluyinka Adewumi & Olawale Joshua Adeleke, 2018. "A survey of recent advances in vehicle routing problems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(1), pages 155-172, February.
    20. K Fagerholt & B A Foss & O J Horgen, 2009. "A decision support model for establishing an air taxi service: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1173-1182, September.

    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:spr:eurjtl:v:7:y:2018:i:4:d:10.1007_s13676-018-0121-3. 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.