3rd International ICST Conference on Simulation Tools and Techniques

Research Article

Simulation of a large scale dynamic pickup and delivery problem

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  • @INPROCEEDINGS{10.4108/ICST.SIMUTOOLS2010.8701,
        author={Esa  Hyyti\aa{} and Lauri  H\aa{}me and Aleksi  Penttinen and Reijo  Sulonen},
        title={Simulation of a large scale dynamic pickup and delivery problem},
        proceedings={3rd International ICST Conference on Simulation Tools and Techniques},
        publisher={ICST},
        proceedings_a={SIMUTOOLS},
        year={2010},
        month={5},
        keywords={Vehicle routing dial-a-ride problem},
        doi={10.4108/ICST.SIMUTOOLS2010.8701}
    }
    
  • Esa Hyytiä
    Lauri Häme
    Aleksi Penttinen
    Reijo Sulonen
    Year: 2010
    Simulation of a large scale dynamic pickup and delivery problem
    SIMUTOOLS
    ICST
    DOI: 10.4108/ICST.SIMUTOOLS2010.8701
Esa Hyytiä1,*, Lauri Häme1,*, Aleksi Penttinen1,*, Reijo Sulonen1,*
  • 1: Aalto University, School of Science and Technology, PO Box 11000, FI-00076 Aalto, Finland.
*Contact email: esa.hyytia@tkk.fi, lauri.hame@tkk.fi, aleksi.penttinen@tkk.fi, reijo.sulonen@tkk.fi

Abstract

We study a variant of dynamic vehicle routing problem with pickups and deliveries where a vehicle is allocated to each service (i.e., trip) request immediately upon the arrival of the request. Solutions to this problem can be characterized as dynamic policies that define how each customer is handled by operating a fleet of vehicles. Evaluation of such policies is beyond the grasp of analytical studies and requires extensive simulations. We present an efficient and modular simulation tool developed for studying the performance of a large scale system with different policies under given trip arrival process. Numerical and analytical observations on the model are utilized to provide guidelines for solving the routing problem efficiently, and to support the validation of the simulation results. Application of the developed framework is demonstrated by several numerical examples, e.g., policy parameter optimization, which all give insight on the viability of this type of transportation system.