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The on-demand bus routing problem: A large neighborhood search heuristic for a dial-a-ride problem with bus station assignment

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  • MELIS, Lissa
  • SÖRENSEN, Kenneth

Abstract

We introduce a novel optimization problem to support the planning and routing of ondemand buses in an urban context. We call this problem the on-demand bus routing problem. Given are a fl eet of identical buses with fixed capacity, a set of bus stations and travel times between them, and a set of transportation requests. Each transportation request consists of a set of potential departure and a set of potential arrival bus stations, as well as a time window, i.e., an earliest departure time and a latest arrival time. The aim of the on-demand bus routing problem is to (1) assign each passenger to a departure and arrival bus station and (2) develop a set of bus routes to fulfill each request in time while minimizing the total travel time of all users. We present the on-demand bus routing problem, as well as a straightforward large neighborhood search heuristic to solve it. The results found by the heuristic for the on-demand bus system are compared to those of a simulated traditional public bus system with fixed lines and timetables. A thorough analysis of the comparison demonstrates that total user ride times can be significantly lower in an on-demand public bus system and shows that an on-demand bus system works best with a large number of small buses.

Suggested Citation

  • MELIS, Lissa & SÖRENSEN, Kenneth, 2020. "The on-demand bus routing problem: A large neighborhood search heuristic for a dial-a-ride problem with bus station assignment," Working Papers 2020005, University of Antwerp, Faculty of Business and Economics.
  • Handle: RePEc:ant:wpaper:2020005
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    References listed on IDEAS

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    Cited by:

    1. MELIS, Lissa & QUEIROZ, Michell & SÖRENSEN, kenneth, 2021. "The integrated on-demand bus routing problem," Working Papers 2021004, University of Antwerp, Faculty of Business and Economics.

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    Keywords

    Transportation; Routing; Public transport; Metaheuristic;
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