Order Picking Optimization Using the ACO (Ant Colony Optimization) Algorithm in a School Distribution Center

Conde A.S.; Palomino N.M.; Rivera A.V. · Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI (2025) · DOI: 10.1109/coniiti68560.2025.11366129

Resumen

Order picking is one of the most critical and costly logistics operations in distribution centers due to its high demand for time, human resources, and precision. Any inefficiency negatively affects the entire supply chain. This paper addresses the optimization of picking routes in a warehouse through the implementation of an Ant Colony Optimization (ACO) algorithm, which solves the Travelling Salesman Problem (TSP) adapted to the warehouse layout. The model incorporates environment-specific parameters, such as an adjacency matrix and selected nodes based on demand analysis. The optimal route generated was compared, via simulation, with traditional routing methods: largest gap, combined, and S-shape. Results show that the ACO algorithm outperforms these approaches in terms of efficiency, reducing travel time per order by up to 10.59% compared to the combined method and improving picking productivity by more than 37%. Additionally, this solution model is enhanced with complementary tools such as 5S and anthropometric workstation design. This comprehensive approach demonstrates the potential of bioinspired techniques in real operational environments, with scalable benefits for other distribution centers with similar characteristics.

Instituciones: Universidad Peruana de Ciencias Aplicadas