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Vehicle Scheduling and Location Planning of the Charging Infrastructure for Electric Buses Under the Consideration of Partial Charging of Vehicle Batteries

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Operations Research Proceedings 2019

Part of the book series: Operations Research Proceedings ((ORP))

Abstract

To counteract the constantly increasing CO2 emissions, especially in local public transport, more environmentally friendly electric buses are intended to gradually replace buses with combustion engines. However, their current short range makes charging infrastructure planning indispensable. For a cost-minimal allocation of electric vehicles to service trips, the consideration of vehicle scheduling is also crucial. This paper addresses the modeling and implementation of a simultaneous solution method for vehicle scheduling and charging infrastructure planning for electric buses. The Savings algorithm is used to construct an initial solution, while the Variable Neighborhood Search serves as an improvement heuristic. The focus is on a comparison between partial and complete charging processes of the vehicle battery within the solution method. An evaluation based on real test instances shows that the procedure implemented leads to large cost savings. Oftentimes, the consideration of partial charging processes is superior to the exclusive use of complete charging processes.

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Notes

  1. 1.

    This corresponds to a saving of 5.9 million monetary units.

  2. 2.

    The maximum number of iterations is selected as the termination criterion.

  3. 3.

    For the maximum neighborhood size, the number of vehicle rotations used within the initial solution is used. For example, if k max = 20%, the neighborhood can increase to 20% of the rotations used.

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Correspondence to Luisa Karzel .

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Karzel, L. (2020). Vehicle Scheduling and Location Planning of the Charging Infrastructure for Electric Buses Under the Consideration of Partial Charging of Vehicle Batteries. In: Neufeld, J.S., Buscher, U., Lasch, R., Möst, D., Schönberger, J. (eds) Operations Research Proceedings 2019. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-48439-2_5

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