The first- and last-mile transport problem remains a significant barrier to the effectiveness and attractiveness of public transport. Demand-Responsive Feeder Transit (DRFT) has emerged as a promising solution, but its efficiency and effectiveness depend on designing efficient routes. This chapter develops an integer programming model to optimize DRFT routing by incorporating multi-passenger ride-sharing and route travel time constraints. The objective is to minimize total system costs, encompassing fleet size, operational expenses, and penalties for deviations from passengers’ desired boarding times. Given the problem’s computational complexity, a tailored metaheuristic algorithm is proposed to achieve efficient solutions for large-scale, real-world instances. A case study demonstrates the model’s effectiveness and efficacy in balancing operational efficiency with passenger service quality. The results confirm the approach’s potential to significantly reduce costs while improving service quality. The chapter concludes with discussions on further extensions, including the consideration of flexible stop selection.