Record link: 
http://hdl.handle.net/20.500.12708/191300
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Title: 
A Large Neighborhood Search for Battery Swapping Station Location Planning for Electric Scooters
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Citation: 
Jatschka, T., Rauscher, M., Kreutzer, B., Okamoto, Y., Kataoka, H., Rodemann, T., & Raidl, G. R. (2022). A Large Neighborhood Search for Battery Swapping Station Location Planning for Electric Scooters. In R. Moreno-Díaz, F. Pichler, & A. Quesada-Arencibia (Eds.), Computer Aided Systems Theory – EUROCAST 2022 : 18th International Conference, Las Palmas de Gran Canaria, Spain, February 20–25, 2022, Revised Selected Papers (pp. 121–129). Springer. https://doi.org/10.1007/978-3-031-25312-6_14
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Publisher DOI: 
10.1007/978-3-031-25312-6_14
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Jatschka, Thomas 
Rauscher, Matthias 
Kreutzer, Bernhard 
Okamoto, Yusuke 
Kataoka, Hiroaki 
Rodemann, Tobias 
Raidl, Günther R. 
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Organisational Unit: 
E192-01 - Forschungsbereich Algorithms and Complexity 
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Published in: 
Computer Aided Systems Theory – EUROCAST 2022 : 18th International Conference, Las Palmas de Gran Canaria, Spain, February 20–25, 2022, Revised Selected Papers 
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ISBN: 
978-3-031-25311-9
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Volume: 
13789
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Date (published): 
2022
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Event name: 
Eurocast 2022. 18th International Conference on Computer Aided Systems Theory 
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Event date: 
20-Feb-2022 - 25-Feb-2022
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Event place: 
Las Palmas de Gran Canaria, Spain
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Number of Pages: 
9
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Publisher: 
Springer, Cham
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Peer reviewed: 
Yes
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Keywords: 
Battery swapping stations; Facility location problem; Large neighborhood search; Mixed integer linear programming
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Abstract: 
We consider the Multi Objective Battery Swapping Station Location Problem (MOBSSLP) for planning the setup of new stations for exchanging depleted batteries of electric scooters with the aim of minimizing a three-part objective function while satisfying an expected amount of demand. Batteries returned at a station are charged and provided to customers again once they are full. We present a large neighborhood search (LNS) for solving MOBSSLP instances. The LNS makes use of a mixed integer linear program (MILP) to quickly find good solutions within a specified neighborhood. Multiple neighborhood structures given by pairs of destroy and repair operators are suggested. The proposed LNS is evaluated on instances generated by adapted approaches from the literature with up to 500 potential station locations and up to 1000 user trips. Solutions obtained from the LNS have on average ten to thirty percent better objective values on these instances than a state-of-the-art MILP solver.
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Research Areas: 
Logic and Computation: 100%
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Science Branch: 
1020 - Informatik: 80%
1010 - Mathematik: 20%
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Appears in Collections:
Conference Paper

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