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A Heuristic Solution Approach for the Optimization of Dynamic Ridesharing Systems

In: Operations Research Proceedings 2019

Author

Listed:
  • Nicolas Rückert

    (Hamburg University of Technology)

  • Daniel Sturm

    (Hamburg University of Technology)

  • Kathrin Fischer

    (Hamburg University of Technology)

Abstract

The key to a successful ridesharing service is an efficient allocation and routing of vehicles and customers. In this paper, relevant aspects from practice, like customer waiting times, are integrated into a mathematical programming model for the operational optimization of a dynamic ridesharing system, improving existing models from the literature. Moreover, a new heuristic solution method for the optimization of a dynamic ridepooling system is developed and compared with the exact solution derived by a MIP solver based on the above-mentioned model. In a case study consisting of 30 customers who request different rides and can be transported by a fleet of 10 vehicles in the area of Hamburg, both approaches are tested. The results show that the heuristic solution method is superior to the exact solution method, especially with respect to the required solution time.

Suggested Citation

  • Nicolas Rückert & Daniel Sturm & Kathrin Fischer, 2020. "A Heuristic Solution Approach for the Optimization of Dynamic Ridesharing Systems," Operations Research Proceedings, in: Janis S. Neufeld & Udo Buscher & Rainer Lasch & Dominik Möst & Jörn Schönberger (ed.), Operations Research Proceedings 2019, pages 733-739, Springer.
    • Handle: RePEc:spr:oprchp:978-3-030-48439-2_89
    DOI: 10.1007/978-3-030-48439-2_89
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