Routing optimization modeling demonstrates an 83% reduction in vehicle requirements for student activity transit, indicating microtransit viability under flexible service parameters.
This study investigates a user-focused microtransit service designed to transport students to after-school activities. The methodology includes generating a synthetic student population and the corresponding trip requests, determining the routes using a metaheuristic approach to solve a Vehicle Routing Problem with Pickup and Delivery and Time Windows (VRPPDTW), and evaluating system performance under a zero-rejection policy. The VRPPDTW includes scheduling drivers with mandatory breaks and maximum shift durations, while minimizing unassigned trips, waiting time, travel time, and route imbalance. The case study focuses on an on-demand transport service for students’ after-school activities in Limassol, Cyprus. Various scenarios are analyzed to assess the effect of fleet size, fare levels, and service parameters on performance. The results show that a fleet of 10 vehicles serving 144 trips for 60 students can reduce the number of cars required by 83%. Larger fleets achieve higher occupancy and better kilometer utilization. Of note, fleets of 20 vehicles or more surpass a system efficiency of one, indicating the distance traveled by the service is lower than individual trips. For service levels, increasing acceptable waiting time by 5 min or travel time by 15 min boosts capacity by 24%. Economically, a zero-rejection policy is sustainable only for large fleets with high fares. However, allowing a small rejection rate of 2% significantly improves viability, enabling the fleet of 10 vehicles to break even with fares 25% lower than local taxi rates.
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Patricio et al. (2026) studied this question.
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