With the escalating demand for meal delivery services, this study delves into the Meal Delivery Routing Problem (MDRP) within the context of last-mile logis-tics. Focusing on the critical aspects of courier allocation and order fulfillment, we introduce a novel approach utilizing a GRASP metaheuristic. The algorithm optimizes the assignment of couriers to orders, considering dynamic factors such as courier availability, order demands, and geographical locations. Real-world in-stances from a Colombian delivery app form the basis of our computational anal-ysis. Calibration of GRASP parameters reveals a delicate trade-off between solu-tion quality and computational time. Comparative results with a simulation-optimization based study underscore GRASP's competitive performance, demon-strating strengths in fulfilling orders and routing efficiency across diverse in-stances. This research enhances operational efficiency in the burgeoning food de-livery industry, shedding light on practical algorithms for last-mile logistics opti-mization.