Abstract
This work considers an approach called Bacterial Antibiotic Resistance 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 non-resistant 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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Dorigo, M., Stuetzle, T.: Ant Colony Optimization, 5th edn. A Bradford Book, Cambridge (2004)
Du, K.-L., Swamy, M.N.S.: Search and Optimization by Metaheuristics. Birkhauser, Basel (2016)
Kramer, O.: Genetic Algorithm Essentials. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-52156-5
Michalewicz, Z., Fogel, D.: How to Solve It: Modern Heuristics, 2nd edn. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-662-07807-5
Niu, B., Chan, F.T.S., Xie, T., Liu, Y.: Guided chemotaxis-based bacterial colony algorithm for three-echelon supply chain optimisation. Int. J. Comput. Integr. Manuf. 30(2–3), 305–319 (2017)
Snyder, L., Peters, J.E., Henken, T.M., Champness, W.: Molecular Genetics of Bacteria, 4th edn. ASM Press, Washington, D.C. (2013)
Talbi, E.G.: Metaheuristics: From Design to Implementation. Wiley, New York (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Pinninghoff J., M.A., Orellana M., J., Contreras A., R. (2019). Bacterial Resistance Algorithm. An Application to CVRP. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) From Bioinspired Systems and Biomedical Applications to Machine Learning. IWINAC 2019. Lecture Notes in Computer Science(), vol 11487. Springer, Cham. https://doi.org/10.1007/978-3-030-19651-6_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-19651-6_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-19650-9
Online ISBN: 978-3-030-19651-6
eBook Packages: Computer ScienceComputer Science (R0)