Metaheurísticos para Solución del Problema de Ruteo en la Recuperación de Medicamentos Sobrantes y Suministros en Hospitales

This article aims to formulate and solve a routing problem for the collection of surplus leftover medicines and supplies in the minimum possible time. To solve the problem, two metaheuristics called simulated annealing (RS) and particle swarm optimization (PSO) are applied. Additionally, factors such as collection list size (TLR), size of collection car fleet (TFCR), as well as hospital room quantities are modeled. From the experimental validation it was detected that the levels of the PSO metaheuristic with the TLR level of 250 products, generates shorter collection times with values of 58.30 and 57.30 minutes / set of routes. Meanwhile, a combination of the TLR levels of 400 products, with the RS metaheuristic, produces the lowest average routing time with values of 99.33 and 101.24 minutes / set of routes. These results showed the effectiveness of metaheuristics to solve the problem of routing in hospital logistics.