This paper addresses the application of the sparrow search algorithm to the vehicle routing problem, specifically within the context of last-mile delivery. The primary objective is to optimize delivery routes by minimizing the total delivery time. The sparrow search algorithm, a bio-inspired algorithm that mimics the food-searching behavior of sparrows, was adapted to solve the vehicle routing problem, representing each solution as a permutation of the customers to visit. Key parameters, such as population size, producer ratios, and warning thresholds, were adjusted to balance solution quality and computational efficiency. The methodology included a performance comparison of the bio-inspired algorithm using 40 scenarios with different parameter configurations. The results indicate that sparrow search algorithm is competitive, matching the performance of an exact method in terms of solution quality, particularly in larger instances. Sparrow search algorithm proves to be a flexible and effective option for optimizing the vehicle routing problem, especially in scenarios where parameter tuning is possible.