Abstract
The management of solid waste is of great importance to avoid floods, infections and respiratory diseases, for this reason the present research aimed to develop a route planner for the collection of solid waste in the city of Huánuco, using general algorithms. Ethics. In addition, the study was of a quantitative-experimental approach. The following techniques and instruments were used to collect the information: scientific observation because we will examine the external reality in order to obtain the data in advance, observation guide to record evidence of solid waste collection, which was validated using the expert technique, who evidenced the existing relationship between the proposed objectives, categories, indicators, items and response options considering their coherence, relevance and writing The population was made up of 192,627 inhabitants of the city de Huánuco, The results of the tests show the effectiveness of the genetic algorithm with a population of 4 vehicles, in which lower cost values were obtained, and with respect to the execution time, a greater number of destinations. The graph was constructed by gathering information from the streets and/or avenues of the Huánuco district such as addresses, coordinates, and street intersections, through the Google Maps map provider through an Adjacency matrix, to then run the Genetic Algorithm.
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
Bernays, E.L.: Public Relations Idea book. Printers In Pub. Co, USA (1958)
Botto, M.: La comunicación en las instituciones educativas de nivel (2011)
Goldberg D.: Genetic Algorithms in Search, Optimization and Machine Learning, 1st. edn.). Addison-Wesley Longman Publishing Co., Inc., Boston (1989). ISBN:978–0–201–15767Digital Library, https://dl.acm.org/doi/book/https://doi.org/10.5555/534133
Hermitaño, M.: Optimización de rutas para la recolección de residuos sólidos con uso de contenedores aplicando el algoritmo colonia de hormigas en la ciudad de Huaraz. Universidad Nacional Santiago Antunez de Mayola. Repositorio Institucional NASAM (2019). http://repositorio.unasam.edu.pe/handle/UNASAM/4056
Manrique, F.: Sistema de recojo de residuos sólidos domiciliarios y sus efectos ambientales y económicos en el distrito de Pocollay. Universidad Privada de Tacna. Repositorio Institucional UPT (2020). http://repositorio.upt.edu.pe/handle/UPT/1660
MINAM: Nueva ley de residuos sólidos (2020). https://www.minam.gob.pe/gestion-de-residuos-solidos/nueva-ley-de-residuos-solidos/
Arkhipov D., Wu, D., Wu, T., Regan, A.C.: Un marco de algoritmo genético paralelo para la planificación del transporte y la gestión logística. IEEE Access 8, 106506–106515 (2020). 10.1109 / ACCESS.2020.2997812
Petriv, C.: Algoritmos genéticos aplicados a soluciones logísticas de sanidad. Centri Educativo de las Fuerzas Armadas de Argentina. Trabajos Finales Integradores de Especialización Repositorio Digital CEFA (2012). http://cefadigital.edu.ar/handle/1847939/285
Nanayakkara, S., Srinivasan, D., Wei, L., German, X., Taylor, E., Yong, S.H.: Planificador de rutas basado en algoritmos genéticos para grandes redes de calles urbanas. In: Congreso IEEE sobre Computación Evolutiva, pp. 4469–4474. Repositorio institucional IEEE (2007). 10.1109 / CEC.2007.4425056, https://ieeexplore.ieee.org/document/4425056
Li, Q., Liu, G., Zhang, W., Zhao, C., Yin, Y., Wang, Z.: A specific genetic algorithm for optimum path planning in intelligent transportation system.In: 6th International Conference on its Telecommunications, pp. 140–143 (2006). 10.1109 / ITST.2006.288799
Saminef: Planificación y estudio de rutas. LOCOEX (ASCOEL S.A.L.) LOGÍSTICA Y COMERCIO (2020). https://logisticaascoel.com/planificacion-estudio-rutas/
Schmitt, M.: Theory of genetic algorithms. Theoretical Computer Science (2001)
Castillo, J.: Implementación de un algoritmo genético para elaborar un conjunto de rutas óptimas para el transporte de la comunidad universitaria desde y hacia el campus principal. Pontificia Universidad Catolica del Perú. Repositorio Institucional PUCP (2018). https://tesis.pucp.edu.pe/repositorio/handle/20.500.12404/13047
Moratilla, A., Fernández, E., Sánchez, J.J., Borja, V.: Selection optimal number of operators for the treatment of VRP problems with Genetic algorithms (2014)
Ikeda, Y., Inoue, M.: An Evacuation Route Planning for Safety Route Guidance System after Natural Disaster Using Multi-Objective Genetic Algorithm. Procedia Comput. Sci. 96, 1323–1331 (2016). https://doi.org/10.1016/j.procs.2016.08.177
Zhang, X., Chen, Y., Li, T.: Optimization of logistics route based on Dijkstra. In: Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS, 2015–Novem(1), pp. 313–316 (2015). https://doi.org/10.1109/ICSESS.2015.7339063
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Reyna-González, J.E., Gómez Fuertes, A., Reyes Pérez, M.D., Carrión-Barco, G., Piscoya Vargas, C.A. (2021). Genetic Algorithm to Plan Routes. Case: Waste Collectors - Huanuco, Peru. 2020. In: Stephanidis, C., et al. HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence. HCII 2021. Lecture Notes in Computer Science(), vol 13095. Springer, Cham. https://doi.org/10.1007/978-3-030-90963-5_40
Download citation
DOI: https://doi.org/10.1007/978-3-030-90963-5_40
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-90962-8
Online ISBN: 978-3-030-90963-5
eBook Packages: Computer ScienceComputer Science (R0)