Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection

Hugo Vega-Huerta; Jordy Mayhuay Marcos; Marx Campos Acosta; Xavier Villanueva Monrroy; Gisella Luisa Elena Maquen-Niño; María Puelles-Bulnes; Rubén Gil-Calvo

doi:10.1007/978-981-97-3859-5_31

Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection

Hugo Vega-Huerta, Jordy Mayhuay Marcos, Marx Campos Acosta, Xavier Villanueva Monrroy, Gisella Luisa Elena Maquen-Niño, María Puelles-Bulnes, Rubén Gil-Calvo

Computer and Informatics Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The district of San Juan de Lurigancho (SJL) in Lima—Peru, is one of the districts crowed in the capital and has one of the highest amounts solid domestic wastes. To fix this problem, a model was developed to map the distance and calculate the best route to collect the domes-tic solid waste in the whole San Carlos neighborhood in SJL district. Our model was developed using genetic algorithms in JavaScript with Node JS to calculate the shortest path. For the data visualization was used the React JS for the frontend and Google Maps API for the display of an interactive map. The results obtained allowed were able to find an optimal route that joins two opposite points within the map of the San Carlos neighborhood, which is made up of 5 nodes and measures 514 m away. The model developed could generate populations of 10 to 100 individuals with the map nodes through selection, crossing and mutation processes, obtaining an optimal route that facilitates the domestic waste collection processes with the shortest distance.

Original language	English
Title of host publication	Proceedings of 8th ASRES International Conference on Intelligent Technologies - ICIT 2023
Editors	Vipin Kumar Tripathi, Karm Veer Arya, Ciro Rodriguez
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	389-400
Number of pages	12
ISBN (Print)	9789819738588
DOIs	https://doi.org/10.1007/978-981-97-3859-5_31
State	Published - 2025
Event	8th International Conference on Intelligent Technologies, ICIT 2023 - Jakarta, Indonesia Duration: 15 Dec 2023 → 17 Dec 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1031
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	8th International Conference on Intelligent Technologies, ICIT 2023
Country/Territory	Indonesia
City	Jakarta
Period	15/12/23 → 17/12/23

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

Keywords

Collection
Genetic algorithm
Minimum route
Pathfinding
Solid waste

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-981-97-3859-5_31

Cite this

Vega-Huerta, H., Marcos, J. M., Acosta, M. C., Monrroy, X. V., Maquen-Niño, G. L. E., Puelles-Bulnes, M., & Gil-Calvo, R. (2025). Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection. In V. K. Tripathi, K. V. Arya, & C. Rodriguez (Eds.), Proceedings of 8th ASRES International Conference on Intelligent Technologies - ICIT 2023 (pp. 389-400). (Lecture Notes in Networks and Systems; Vol. 1031). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-97-3859-5_31

Vega-Huerta, Hugo ; Marcos, Jordy Mayhuay ; Acosta, Marx Campos et al. / Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection. Proceedings of 8th ASRES International Conference on Intelligent Technologies - ICIT 2023. editor / Vipin Kumar Tripathi ; Karm Veer Arya ; Ciro Rodriguez. Springer Science and Business Media Deutschland GmbH, 2025. pp. 389-400 (Lecture Notes in Networks and Systems).

@inproceedings{158fe75755714f54b3a6961b7a8307ab,

title = "Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection",

abstract = "The district of San Juan de Lurigancho (SJL) in Lima—Peru, is one of the districts crowed in the capital and has one of the highest amounts solid domestic wastes. To fix this problem, a model was developed to map the distance and calculate the best route to collect the domes-tic solid waste in the whole San Carlos neighborhood in SJL district. Our model was developed using genetic algorithms in JavaScript with Node JS to calculate the shortest path. For the data visualization was used the React JS for the frontend and Google Maps API for the display of an interactive map. The results obtained allowed were able to find an optimal route that joins two opposite points within the map of the San Carlos neighborhood, which is made up of 5 nodes and measures 514 m away. The model developed could generate populations of 10 to 100 individuals with the map nodes through selection, crossing and mutation processes, obtaining an optimal route that facilitates the domestic waste collection processes with the shortest distance.",

keywords = "Collection, Genetic algorithm, Minimum route, Pathfinding, Solid waste",

author = "Hugo Vega-Huerta and Marcos, {Jordy Mayhuay} and Acosta, {Marx Campos} and Monrroy, {Xavier Villanueva} and Maquen-Ni{\~n}o, {Gisella Luisa Elena} and Mar{\'i}a Puelles-Bulnes and Rub{\'e}n Gil-Calvo",

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Vega-Huerta, H, Marcos, JM, Acosta, MC, Monrroy, XV, Maquen-Niño, GLE, Puelles-Bulnes, M & Gil-Calvo, R 2025, Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection. in VK Tripathi, KV Arya & C Rodriguez (eds), Proceedings of 8th ASRES International Conference on Intelligent Technologies - ICIT 2023. Lecture Notes in Networks and Systems, vol. 1031, Springer Science and Business Media Deutschland GmbH, pp. 389-400, 8th International Conference on Intelligent Technologies, ICIT 2023, Jakarta, Indonesia, 15/12/23. https://doi.org/10.1007/978-981-97-3859-5_31

Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection. / Vega-Huerta, Hugo; Marcos, Jordy Mayhuay; Acosta, Marx Campos et al.
Proceedings of 8th ASRES International Conference on Intelligent Technologies - ICIT 2023. ed. / Vipin Kumar Tripathi; Karm Veer Arya; Ciro Rodriguez. Springer Science and Business Media Deutschland GmbH, 2025. p. 389-400 (Lecture Notes in Networks and Systems; Vol. 1031).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection

AU - Vega-Huerta, Hugo

AU - Marcos, Jordy Mayhuay

AU - Acosta, Marx Campos

AU - Monrroy, Xavier Villanueva

AU - Maquen-Niño, Gisella Luisa Elena

AU - Puelles-Bulnes, María

AU - Gil-Calvo, Rubén

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

PY - 2025

Y1 - 2025

N2 - The district of San Juan de Lurigancho (SJL) in Lima—Peru, is one of the districts crowed in the capital and has one of the highest amounts solid domestic wastes. To fix this problem, a model was developed to map the distance and calculate the best route to collect the domes-tic solid waste in the whole San Carlos neighborhood in SJL district. Our model was developed using genetic algorithms in JavaScript with Node JS to calculate the shortest path. For the data visualization was used the React JS for the frontend and Google Maps API for the display of an interactive map. The results obtained allowed were able to find an optimal route that joins two opposite points within the map of the San Carlos neighborhood, which is made up of 5 nodes and measures 514 m away. The model developed could generate populations of 10 to 100 individuals with the map nodes through selection, crossing and mutation processes, obtaining an optimal route that facilitates the domestic waste collection processes with the shortest distance.

AB - The district of San Juan de Lurigancho (SJL) in Lima—Peru, is one of the districts crowed in the capital and has one of the highest amounts solid domestic wastes. To fix this problem, a model was developed to map the distance and calculate the best route to collect the domes-tic solid waste in the whole San Carlos neighborhood in SJL district. Our model was developed using genetic algorithms in JavaScript with Node JS to calculate the shortest path. For the data visualization was used the React JS for the frontend and Google Maps API for the display of an interactive map. The results obtained allowed were able to find an optimal route that joins two opposite points within the map of the San Carlos neighborhood, which is made up of 5 nodes and measures 514 m away. The model developed could generate populations of 10 to 100 individuals with the map nodes through selection, crossing and mutation processes, obtaining an optimal route that facilitates the domestic waste collection processes with the shortest distance.

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SN - 9789819738588

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BT - Proceedings of 8th ASRES International Conference on Intelligent Technologies - ICIT 2023

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Vega-Huerta H, Marcos JM, Acosta MC, Monrroy XV, Maquen-Niño GLE, Puelles-Bulnes M et al. Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection. In Tripathi VK, Arya KV, Rodriguez C, editors, Proceedings of 8th ASRES International Conference on Intelligent Technologies - ICIT 2023. Springer Science and Business Media Deutschland GmbH. 2025. p. 389-400. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-97-3859-5_31

Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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Cite this