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AuthorMasoud, Mahmoud
AuthorElhenawy, Mohammed
AuthorLiu, Shi Qiang
AuthorAlmannaa, Mohammed
AuthorGlaser, Sebastien
AuthorAlhajyaseen, Wael
Available date2023-04-05T10:30:43Z
Publication Date2023-01-18
Publication NameSustainability (Switzerland)
Identifierhttp://dx.doi.org/10.3390/su15031869
CitationMasoud, M., Elhenawy, M., Liu, S. Q., Almannaa, M., Glaser, S., & Alhajyaseen, W. (2023). A Simulated Annealing for Optimizing Assignment of E-Scooters to Freelance Chargers. Sustainability, 15(3), 1869.
ISSN2071-1050
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85147866169&origin=inward
URIhttp://hdl.handle.net/10576/41696
AbstractFirst- and last-mile trips are becoming increasingly expensive and detrimental to the environment, especially within dense cities. Thus, new micro-mobility transportation modes such as e-scooter sharing systems have been introduced to fill the gaps in the transportation network. Furthermore, some recent studies examined e-scooters as a green option from the standpoint of environmental sustainability. Currently, e-scooter charging is conducted by competitive freelancers who do not consider the negative environmental impact resulting from not optimizing the fuel efficiency of their charging trips. Several disputes have been recorded among freelance chargers, especially when simultaneously arriving at an e-scooters location. The paper aims to find the optimal tours for all chargers to pick up e-scooters in the form of routes, such that each route contains one charger, and each e-scooter is visited only once by the set of routes, which are typically called an E-Scooter-Chargers Allocation (ESCA) solution. This study develops a mathematical model for the assignment of e-scooters to freelance chargers and adapts a simulated annealing metaheuristic to determine a near-optimal solution. We evaluated the proposed approach using real-world instances and a benchmark-simulated dataset. Moreover, we compare the proposed model benchmark dataset to the baseline (i.e., state-of-practice). The results show a reduction of approximately 61–79% in the total distance traveled, leading to shorter charging trips.
SponsorThe authors would like to acknowledge the financial and in-kind support from the Centre for Accident Research and Road Safety at the Queensland University of Technology, Brisbane, Australia.
Languageen
PublisherMultidisciplinary Digital Publishing Institute (MDPI)
Subjectassignment problem
e-scooters
freelancers
micro-mobility
simulated annealing
TitleA Simulated Annealing for Optimizing Assignment of E-Scooters to Freelance Chargers
TypeArticle
Issue Number3
Volume Number15
ESSN2071-1050
dc.accessType Open Access


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