A Simulated Annealing for Optimizing Assignment of E-Scooters to Freelance Chargers

Mahmoud Masoud (), Mohammed Elhenawy, Shi Qiang Liu, Mohammed Almannaa, Sebastien Glaser and Wael Alhajyaseen
Additional contact information
Mahmoud Masoud: Centre for Accident Research and Road Safety, Queensland University of Technology, Brisbane 4059, Australia
Mohammed Elhenawy: Centre for Accident Research and Road Safety, Queensland University of Technology, Brisbane 4059, Australia
Shi Qiang Liu: School of Economics and Management, Fuzhou University, Fuzhou 350105, China
Mohammed Almannaa: Department of Civil Engineering, College of Engineering, King Saud University, P.O. Box 2454, Riyadh 11451, Saudi Arabia
Sebastien Glaser: Centre for Accident Research and Road Safety, Queensland University of Technology, Brisbane 4059, Australia
Wael Alhajyaseen: Qatar Transportation and Traffic Safety Center, College of Engineering, Qatar University, Doha P.O. Box 2713, Qatar

Sustainability, 2023, vol. 15, issue 3, 1-15

Abstract: First- 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.

Keywords: micro-mobility; e-scooters; freelancers; simulated annealing; assignment problem (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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