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A new mixed integer linear model for a rich vehicle routing problem with docking constraints

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  • Julia Rieck
  • Jürgen Zimmermann

Abstract

In this paper we address a rich vehicle routing problem that arises in real-life applications. Among other aspects we consider time windows, simultaneous delivery and pick-up at customer locations and multiple use of vehicles. To guarantee a coordinated material flow at the depot, we include the timed allocation of vehicles to loading bays at which the loading and unloading activities can occur. The resulting vehicle routing problem is formulated as a two-index vehicle-flow model which integrates the routing under real-life conditions and the assignment of vehicles to loading bays at the depot. We use CPLEX 11.0 to solve medium-sized instances that are derived from the extended Solomon test set. The selective implementation of preprocessing techniques and cutting planes improves the solver performance significantly. Copyright Springer Science+Business Media, LLC 2010

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  • Julia Rieck & Jürgen Zimmermann, 2010. "A new mixed integer linear model for a rich vehicle routing problem with docking constraints," Annals of Operations Research, Springer, vol. 181(1), pages 337-358, December.
    • Handle: RePEc:spr:annopr:v:181:y:2010:i:1:p:337-358:10.1007/s10479-010-0748-4
    DOI: 10.1007/s10479-010-0748-4
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    References listed on IDEAS

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    1. Brian Kallehauge & Jesper Larsen & Oli B.G. Madsen & Marius M. Solomon, 2005. "Vehicle Routing Problem with Time Windows," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 67-98, Springer.
    2. Julia Rieck & Jürgen Zimmermann, 2009. "A Hybrid Algorithm for Vehicle Routing of Less-Than-Truckload Carriers," Lecture Notes in Economics and Mathematical Systems, in: Kenneth Sörensen & Marc Sevaux & Walter Habenicht & Martin Josef Geiger (ed.), Metaheuristics in the Service Industry, chapter 9, pages 155-171, Springer.
    3. 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.
    4. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    5. Goel, Asvin & Gruhn, Volker, 2008. "A General Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 191(3), pages 650-660, December.
    6. Moshe Dror, 1994. "Note on the Complexity of the Shortest Path Models for Column Generation in VRPTW," Operations Research, INFORMS, vol. 42(5), pages 977-978, October.
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    Cited by:

    1. Oscar Dominguez & Angel A. Juan & Barry Barrios & Javier Faulin & Alba Agustin, 2016. "Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet," Annals of Operations Research, Springer, vol. 236(2), pages 383-404, January.
    2. Jose Carlos Molina & Ignacio Eguia & Jesus Racero, 2018. "An optimization approach for designing routes in metrological control services: a case study," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 924-952, December.
    3. Puca Huachi Vaz Penna & Anand Subramanian & Luiz Satoru Ochi & Thibaut Vidal & Christian Prins, 2019. "A hybrid heuristic for a broad class of vehicle routing problems with heterogeneous fleet," Annals of Operations Research, Springer, vol. 273(1), pages 5-74, February.
    4. Lahyani, Rahma & Khemakhem, Mahdi & Semet, Frédéric, 2015. "Rich vehicle routing problems: From a taxonomy to a definition," European Journal of Operational Research, Elsevier, vol. 241(1), pages 1-14.
    5. Oscar Dominguez & Angel Juan & Barry Barrios & Javier Faulin & Alba Agustin, 2016. "Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet," Annals of Operations Research, Springer, vol. 236(2), pages 383-404, January.
    6. Max Leyerer & Marc-Oliver Sonneberg & Maximilian Heumann & Tim Kammann & Michael H. Breitner, 2019. "Individually Optimized Commercial Road Transport: A Decision Support System for Customizable Routing Problems," Sustainability, MDPI, vol. 11(20), pages 1-21, October.
    7. Nasrin Asgari & Mohsen Rajabi & Masoumeh Jamshidi & Maryam Khatami & Reza Zanjirani Farahani, 2017. "A memetic algorithm for a multi-objective obnoxious waste location-routing problem: a case study," Annals of Operations Research, Springer, vol. 250(2), pages 279-308, March.
    8. Ramos, Tânia Rodrigues Pereira & Gomes, Maria Isabel & Barbosa-Póvoa, Ana Paula, 2014. "Planning a sustainable reverse logistics system: Balancing costs with environmental and social concerns," Omega, Elsevier, vol. 48(C), pages 60-74.
    9. Michael Drexl, 2012. "Branch-and-Cut Algorithms for the Vehicle Routing Problem with Trailers and Transshipments," Working Papers 1210, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    10. Du, Jia Yan & Brunner, Jens O. & Kolisch, Rainer, 2014. "Planning towing processes at airports more efficiently," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 293-304.

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