2021-06-102021-04-12http://hdl.handle.net/10784/29846Neuromedica is a Colombian pharmacy which provides treatment for people with neurological diseases. Recently, Neuromedica started attending patients from other pharmacy which led to a significant increase in the waiting time. In this pharmacy, people are classified and attended due to certain priorities. The data, given by Neuromedica, is analyzed using boxplots, Kruskal-Wallis and Kolmogorov-Smirnov tests with Python’s library Scipy. The objective of this work is to determine the number of assistants and queue logistic such that the waiting time has a significant reduction, with the purpose to provide a satisfactory level of service. A discrete-event simulation model was created and implemented in Python. A heuristic approach to minimize the waiting time is used. Additionally, a sensitivity analysis is made on the assumed distributions.application/pdfenginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessComplex system modelingQueue theoryDiscrete-event simulationSimulation-optimizationStatistical analysis of input-output dataWhite and black-box validationConceptual modelingPythonAcceso abierto2021-06-10Plazas Escudero, DavidCárdenas-Rodríguez, Juan SebastianRestrepo Sierra, Mateo