Bacterial resistance algorithm. An application to CVRP

• Autores: M.Angélica. Pinninghoff J., José Orellana Yáñez, Ricardo Contreras Soto
• Localización: From Bioinspired Systems and Biomedical Applications to Machine Learning: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019, Almería, Spain, June 3–7, 2019, Proceedings, Part II / coord. por Hojjat Adeli; José Manuel Ferrández Vicente (dir. congr.), José Ramón Álvarez Sánchez (dir. congr.), Félix de la Paz López (dir. congr.), Francisco Javier Toledo Moreo (dir. congr.), 2019, ISBN 978-3-030-19651-6, págs. 204-211
• Idioma: inglés
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• Resumen

  • This work considers an approach called Bacterial AntibioticResistance Algorithm (BARA) in which a bacteria colony represents a set of candidates solutions subjected to the presence of an antibiotic as a pressure factor for separating good and wrong answers. In our terms, the classification allows us to have two groups: resistant and nonresistant bacteria. Then, by using genetic variation mechanisms (conjugation, transformation, and mutation), it is expected that non-resistant bacteria may improve their defense capability to enhance their probability of survival. The proposed algorithm implements and evaluates instances of the Capacitated Vehicle Routing Problem (CVRP). Results are comparable to those obtained in similar approaches