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Modelization of Time-Dependent Urban Freight Problems by Using a Multiple Number of Distribution Centers

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  • David Escuín

  • Carlos Millán

  • Emilio Larrodé

Abstract

The aim of the paper is to model urban distribution vehicle routing problems by means of hubs in large cities. The idea behind the urban distribution center (DC) is to provide buffer points where cargo and packages which are to be delivered to shops and businesses can be stored beforehand. At these centers, there will be other kinds of routing problems corresponding to other fairly similar distribution problems. In this paper, a new vehicle routing model (based on the known Time-Dependent Vehicle Routing Problem with Time Windows, TDVRPTW) has been carried out and a change in the traditional approach is proposed, by adopting a system in which some customers are served by urban DCs while remaining customers are served by traditional routes. This study is also motivated by recent developments in real time traffic data acquisition systems, as well as national and international policies aimed at reducing concentrations of greenhouse gases emitted by traditional vans. By using k DCs, the whole problem is now composed of k+1 problems: one special VRPTW for each DC in addition to the main problem, in which some customers and k DC are serviced. The model has been tested by simulating one real case of pharmaceutical distribution within the city of Zaragoza. Copyright The Author(s) 2012

Suggested Citation

  • David Escuín & Carlos Millán & Emilio Larrodé, 2012. "Modelization of Time-Dependent Urban Freight Problems by Using a Multiple Number of Distribution Centers," Networks and Spatial Economics, Springer, vol. 12(3), pages 321-336, September.
    • Handle: RePEc:kap:netspa:v:12:y:2012:i:3:p:321-336
    DOI: 10.1007/s11067-009-9099-6
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    References listed on IDEAS

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    1. Donati, Alberto V. & Montemanni, Roberto & Casagrande, Norman & Rizzoli, Andrea E. & Gambardella, Luca M., 2008. "Time dependent vehicle routing problem with a multi ant colony system," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1174-1191, March.
    2. Naoki Ando & Eiichi Taniguchi, 2006. "Travel Time Reliability in Vehicle Routing and Scheduling with Time Windows," Networks and Spatial Economics, Springer, vol. 6(3), pages 293-311, September.
    3. Mitrovic-Minic, Snezana & Krishnamurti, Ramesh & Laporte, Gilbert, 2004. "Double-horizon based heuristics for the dynamic pickup and delivery problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 38(8), pages 669-685, September.
    4. Francisco Silva & Daniel Serra, 2007. "Incorporating Waiting Time in Competitive Location Models," Networks and Spatial Economics, Springer, vol. 7(1), pages 63-76, March.
    5. Friesz, Terry L. & Mookherjee, Reetabrata & Holguín-Veras, José & Rigdon, Matthew A., 2008. "Dynamic pricing in an urban freight environment," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 305-324, May.
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    Cited by:

    1. Wei Zhou & Jane Lin, 2019. "An On-Demand Same-Day Delivery Service Using Direct Peer-to-Peer Transshipment Strategies," Networks and Spatial Economics, Springer, vol. 19(2), pages 409-443, June.
    2. Magdalena Mucowska, 2021. "Trends of Environmentally Sustainable Solutions of Urban Last-Mile Deliveries on the E-Commerce Market—A Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
    3. Surendra Reddy Kancharla & Gitakrishnan Ramadurai, 2019. "Multi-depot Two-Echelon Fuel Minimizing Routing Problem with Heterogeneous Fleets: Model and Heuristic," Networks and Spatial Economics, Springer, vol. 19(3), pages 969-1005, September.

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