OPTIMAL ASSIGNMENT OF E-SCOOTER TO CHARGERS

Traffic congestion is a daily problem facing commuters in dense cities. This problem is getting worse with the rapid growth of cities' population and migration from rural to urban areas. Recently, electric dock-less scooters have emerged as a micro mobility mode and as a potential solution for large crowded cities with limited resources. However, a question of how to charge these e-scooters has been raised. Many e-scooter companies use freelancers to charge the scooter where they compete to collect and charge the e-scooters at their homes. This competition leads the chargers to travel long distances to collect e-scooters. In this paper, we developed a mixed integer linear programming (MILP) model to solve the E-Scooter-Chargers Allocation problem. The proposed model allocates the escooters to the chargers with a particular emphasis on minimising the chargers' average travelled distance to collect the e-scooters. Moreover, we modelled the charging problem as a game between two sets of disjoint players, namely escooters and chargers. Then we adapted the college admission algorithm (ACA) to solve the assignment problem. For the sake of comparison, we adapted the black hole optimiser (BHO) to solve this problem. The experimental results showed that ACA solutions are close to the optimal solutions found by the MILP. Furthermore, the BHO solutions are not as good as the ACA solutions. So, we recommend using the ACA to find a good solution for very large instances where MILP needs a long time to find the optimal solution.