The rising popularity of shared e-scooters has created a need for an efficient way to match riders with available vehicles in urban areas. This study proposes a new approach that uses simulation to tackle this challenge. Unlike previous research that has focused on allocating infrastructure, our study prioritizes optimizing the allocation of e-scooters to riders, which is an essential gap in the literature. We conducted simulation experiments using three scenarios, considering factors such as total travel time, rider walking distance, and total distance traveled by vehicles. Our findings provide insights into the optimal allocation method for shared e-scooters, which can help urban planners, transportation authorities, and shared mobility service providers make informed decisions to improve rider satisfaction, minimize environmental impact, and ensure operational efficiency in modern urban environments.