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Night makes you beautiful: an optimization approach to overnight joint beautification and relocation in e-scooter sharing

  • Carrese, Stefano
  • d’Andreagiovanni, Fabio
  • Giacchetti, Tommaso
  • Nardin, Antonella
  • Zamberlan, Leonardo
Publication Date
Jul 06, 2020
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Electric scooter (e-scooter) sharing has recently known a wide success around the world, thanks to its ease of use and parking. However, it soon became apparent that many of its users tend to park without caring about road rules, abandoning e-scooters in locations and positions that compromise urban decorum and interfere with pedestrians. Many municipalities have thus taken actions, such as bans and fines, against e-scooter sharing companies. In this work, we address the problem of optimally managing the actions of a set of agents hired by a sharing company expressly for repositioning e-scooters to guarantee urban decorum. We call these agents beautificators, since their fundamental task is to reposition scooters over short distances (even just a few meters), so to fix inappropriate and disordered parking made by users. Specifically, we propose a new Integer Linear Programming model for representing the problem of jointly scheduling and choosing the actions operated overnight by beautificators and relocators (for fleet balancing) in a service area. We also propose a matheuristic for its solution (a genetic algorithm combined with exact optimization-based neighborhood searches). Computational tests on realistic instances show that our new optimization approach can return solutions of higher quality than a state-of-the-art solver.

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