IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v43y2009i1p27-42.html
   My bibliography  Save this article

Hybrid Adaptive Predictive Control for a Dynamic Pickup and Delivery Problem

Author

Listed:
  • Cristián E. Cortés

    (Civil Engineering Department, Universidad de Chile, Avenue Blanco Encalada 2002, Santiago, Chile)

  • Doris Sáez

    (Electrical Engineering Department, Universidad de Chile, Avenue Tupper 2007, Santiago, Chile)

  • Alfredo Núñez

    (Electrical Engineering Department, Universidad de Chile, Avenue Tupper 2007, Santiago, Chile)

  • Diego Muñoz-Carpintero

    (Electrical Engineering Department, Universidad de Chile, Avenue Tupper 2007, Santiago, Chile)

Abstract

This paper presents a hybrid adaptive predictive control approach that includes future information in real-time routing decisions in the context of a dynamic pickup and delivery problem (DPDP). We recognize in this research that when the problem is dynamic, an additional stochastic effect has to be considered within the analytical expression of the objective function for vehicle scheduling and routing, which is the extra cost associated with potential rerouting arising from unknown requests in the future. The major contributions of this paper are: first, the development of a formal adaptive predictive control framework to model the DPDP, and second, the development and coding of an ad hoc particle swarm optimization (PSO) algorithm to efficiently solve it. Predictive state-space formulations are written on the relevant variables (vehicle load and departure time at stops) for the DPDP. Next, an objective function is stated to solve the real-time system when predicting one and two steps ahead in time. A problem-specific PSO algorithm is proposed and coded according to the dynamic formulation. Then, the PSO method is used to validate this approach through a simulated numerical example.

Suggested Citation

  • Cristián E. Cortés & Doris Sáez & Alfredo Núñez & Diego Muñoz-Carpintero, 2009. "Hybrid Adaptive Predictive Control for a Dynamic Pickup and Delivery Problem," Transportation Science, INFORMS, vol. 43(1), pages 27-42, February.
    • Handle: RePEc:inm:ortrsc:v:43:y:2009:i:1:p:27-42
    DOI: 10.1287/trsc.1080.0251
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.1080.0251
    Download Restriction: no
    File URL: https://libkey.io/10.1287/trsc.1080.0251?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
    ---><---

    References listed on IDEAS

    as
    1. R. Montemanni & L. M. Gambardella & A. E. Rizzoli & A. V. Donati, 2005. "Ant Colony System for a Dynamic Vehicle Routing Problem," Journal of Combinatorial Optimization, Springer, vol. 10(4), pages 327-343, December.
    2. Harilaos N. Psaraftis, 1980. "A Dynamic Programming Solution to the Single Vehicle Many-to-Many Immediate Request Dial-a-Ride Problem," Transportation Science, INFORMS, vol. 14(2), pages 130-154, May.
    3. Michel Gendreau & François Guertin & Jean-Yves Potvin & Éric Taillard, 1999. "Parallel Tabu Search for Real-Time Vehicle Routing and Dispatching," Transportation Science, INFORMS, vol. 33(4), pages 381-390, November.
    4. Paolo Toth & Daniele Vigo, 2003. "The Granular Tabu Search and Its Application to the Vehicle-Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 15(4), pages 333-346, November.
    5. Michael Z. Spivey & Warren B. Powell, 2004. "The Dynamic Assignment Problem," Transportation Science, INFORMS, vol. 38(4), pages 399-419, November.
    6. Dimitris J. Bertsimas & Garrett van Ryzin, 1991. "A Stochastic and Dynamic Vehicle Routing Problem in the Euclidean Plane," Operations Research, INFORMS, vol. 39(4), pages 601-615, August.
    7. Chryssi Malandraki & Mark S. Daskin, 1992. "Time Dependent Vehicle Routing Problems: Formulations, Properties and Heuristic Algorithms," Transportation Science, INFORMS, vol. 26(3), pages 185-200, August.
    8. Bertsimas, Dimitris & Van Ryzin, Garrett., 1991. "A stochastic and dynamic vehicle routing problem in the Euclidean plane," Working papers 3286-91., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    9. Swihart, Michael R. & Papastavrou, Jason D., 1999. "A stochastic and dynamic model for the single-vehicle pick-up and delivery problem," European Journal of Operational Research, Elsevier, vol. 114(3), pages 447-464, May.
    10. Huseyin Topaloglu & Warren Powell, 2007. "Incorporating Pricing Decisions into the Stochastic Dynamic Fleet Management Problem," Transportation Science, INFORMS, vol. 41(3), pages 281-301, August.
    11. Soumia Ichoua & Michel Gendreau & Jean-Yves Potvin, 2006. "Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching," Transportation Science, INFORMS, vol. 40(2), pages 211-225, May.
    12. G J King & H Topaloglu, 2007. "Incorporating the pricing decisions into the dynamic fleet management problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(8), pages 1065-1074, August.
    13. Dimitris J. Bertsimas & Garrett van Ryzin, 1993. "Stochastic and Dynamic Vehicle Routing in the Euclidean Plane with Multiple Capacitated Vehicles," Operations Research, INFORMS, vol. 41(1), pages 60-76, February.
    14. Barrett W. Thomas & Chelsea C. White, 2004. "Anticipatory Route Selection," Transportation Science, INFORMS, vol. 38(4), pages 473-487, November.
    15. Huseyin Topaloglu & Warren B. Powell, 2005. "A Distributed Decision-Making Structure for Dynamic Resource Allocation Using Nonlinear Functional Approximations," Operations Research, INFORMS, vol. 53(2), pages 281-297, April.
    16. Miguel Andres Figliozzi & Hani S. Mahmassani & Patrick Jaillet, 2007. "Pricing in Dynamic Vehicle Routing Problems," Transportation Science, INFORMS, vol. 41(3), pages 302-318, August.
    17. M. W. P. Savelsbergh & M. Sol, 1995. "The General Pickup and Delivery Problem," Transportation Science, INFORMS, vol. 29(1), pages 17-29, 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. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    2. Soeffker, Ninja & Ulmer, Marlin W. & Mattfeld, Dirk C., 2022. "Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review," European Journal of Operational Research, Elsevier, vol. 298(3), pages 801-820.
    3. Pillac, Victor & Gendreau, Michel & Guéret, Christelle & Medaglia, Andrés L., 2013. "A review of dynamic vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 225(1), pages 1-11.
    4. Diego Muñoz-Carpintero & Doris Sáez & Cristián E. Cortés & Alfredo Núñez, 2015. "A Methodology Based on Evolutionary Algorithms to Solve a Dynamic Pickup and Delivery Problem Under a Hybrid Predictive Control Approach," Transportation Science, INFORMS, vol. 49(2), pages 239-253, May.
    5. Marlin W. Ulmer & Dirk C. Mattfeld & Felix Köster, 2018. "Budgeting Time for Dynamic Vehicle Routing with Stochastic Customer Requests," Transportation Science, INFORMS, vol. 52(1), pages 20-37, January.
    6. Soumia Ichoua & Michel Gendreau & Jean-Yves Potvin, 2006. "Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching," Transportation Science, INFORMS, vol. 40(2), pages 211-225, May.
    7. Barrett W. Thomas, 2007. "Waiting Strategies for Anticipating Service Requests from Known Customer Locations," Transportation Science, INFORMS, vol. 41(3), pages 319-331, August.
    8. Ghiani, Gianpaolo & Guerriero, Francesca & Laporte, Gilbert & Musmanno, Roberto, 2003. "Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies," European Journal of Operational Research, Elsevier, vol. 151(1), pages 1-11, November.
    9. Lars M. Hvattum & Arne Løkketangen & Gilbert Laporte, 2006. "Solving a Dynamic and Stochastic Vehicle Routing Problem with a Sample Scenario Hedging Heuristic," Transportation Science, INFORMS, vol. 40(4), pages 421-438, November.
    10. Marlin W. Ulmer & Justin C. Goodson & Dirk C. Mattfeld & Marco Hennig, 2019. "Offline–Online Approximate Dynamic Programming for Dynamic Vehicle Routing with Stochastic Requests," Service Science, INFORMS, vol. 53(1), pages 185-202, February.
    11. Nikola Mardešić & Tomislav Erdelić & Tonči Carić & Marko Đurasević, 2023. "Review of Stochastic Dynamic Vehicle Routing in the Evolving Urban Logistics Environment," Mathematics, MDPI, vol. 12(1), pages 1-44, December.
    12. Jürgen Branke & Martin Middendorf & Guntram Noeth & Maged Dessouky, 2005. "Waiting Strategies for Dynamic Vehicle Routing," Transportation Science, INFORMS, vol. 39(3), pages 298-312, August.
    13. Xiong Hao & Yan Huili, 2019. "General Method of Building a Real-Time Optimization Policy for Dynamic Vehicle Routing Problem," Journal of Systems Science and Information, De Gruyter, vol. 7(6), pages 584-598, December.
    14. Barrett W. Thomas & Chelsea C. White, 2004. "Anticipatory Route Selection," Transportation Science, INFORMS, vol. 38(4), pages 473-487, November.
    15. Russell W. Bent & Pascal Van Hentenryck, 2004. "Scenario-Based Planning for Partially Dynamic Vehicle Routing with Stochastic Customers," Operations Research, INFORMS, vol. 52(6), pages 977-987, December.
    16. Sayarshad, Hamid R. & Chow, Joseph Y.J., 2015. "A scalable non-myopic dynamic dial-a-ride and pricing problem," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 539-554.
    17. Joseph Y. J. Chow & Hamid R. Sayarshad, 2016. "Reference Policies for Non-myopic Sequential Network Design and Timing Problems," Networks and Spatial Economics, Springer, vol. 16(4), pages 1183-1209, December.
    18. Soumia Ichoua & Michel Gendreau & Jean-Yves Potvin, 2000. "Diversion Issues in Real-Time Vehicle Dispatching," Transportation Science, INFORMS, vol. 34(4), pages 426-438, November.
    19. Van Woensel, T. & Kerbache, L. & Peremans, H. & Vandaele, N., 2008. "Vehicle routing with dynamic travel times: A queueing approach," European Journal of Operational Research, Elsevier, vol. 186(3), pages 990-1007, May.
    20. Sheridan, Patricia Kristine & Gluck, Erich & Guan, Qi & Pickles, Thomas & Balcıog˜lu, Barış & Benhabib, Beno, 2013. "The dynamic nearest neighbor policy for the multi-vehicle pick-up and delivery problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 178-194.

    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:inm:ortrsc:v:43:y:2009:i:1:p:27-42. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.