Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study: Peru During COVID-19

Luis Ramirez; Manuel Tupia; Rony Cueva

doi:10.1007/978-3-031-98768-7_2

Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study: Peru During COVID-19

Luis Ramirez
, Manuel Tupia
, Rony Cueva

Sección de Ingeniería Informática

Pontifical Catholic Univ. of Peru

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

One of the main logistical problems during the COVID-19 pandemic in many countries worldwide was the movement and delivery of various medical supplies to government hospitals, including vaccines requiring special conditions for their mobilization. Many algorithmic proposals in the literature address this type of problem, such as the Capacitated Vehicle Routing Problem (CVRP), one of the most common problems that swarm intelligence algorithms address. In the present research, using graphs, an algorithmic approach based on Ant Colony Optimization (ACO) is proposed to solve the CVRP, considering constraints on both vehicle capacity and road conditions (additional information). As a case study, the logistic network established for the distribution of vaccines during the pandemic in Peru, among the different regional state hospitals, is taken directly.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Volume 1
Subtítulo de la publicación alojada	Innovative Approaches in AI, IoT, and Software Systems
Editores	Marcelo V. Garcia, John-Paul Reyes, Carlos Nuñez, Carlos Gordón-Gallegos
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	17-34
Número de páginas	18
ISBN (versión impresa)	9783031987670
DOI	https://doi.org/10.1007/978-3-031-98768-7_2
Estado	Publicada - 2026
Evento	6th International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Ambato, Ecuador Duración: 21 oct. 2024 → 25 oct. 2024

Serie de la publicación

Nombre	Lecture Notes in Networks and Systems
Volumen	1516 LNNS
ISSN (versión impresa)	2367-3370
ISSN (versión digital)	2367-3389

Conferencia

Conferencia	6th International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024
País/Territorio	Ecuador
Ciudad	Ambato
Período	21/10/24 → 25/10/24

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

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10.1007/978-3-031-98768-7_2

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Ramirez, L., Tupia, M., & Cueva, R. (2026). Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study: Peru During COVID-19. En M. V. Garcia, J.-P. Reyes, C. Nuñez, & C. Gordón-Gallegos (Eds.), Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Volume 1: Innovative Approaches in AI, IoT, and Software Systems (pp. 17-34). (Lecture Notes in Networks and Systems; Vol. 1516 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-98768-7_2

Ramirez, Luis ; Tupia, Manuel ; Cueva, Rony. / Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study : Peru During COVID-19. Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Volume 1: Innovative Approaches in AI, IoT, and Software Systems. editor / Marcelo V. Garcia ; John-Paul Reyes ; Carlos Nuñez ; Carlos Gordón-Gallegos. Springer Science and Business Media Deutschland GmbH, 2026. pp. 17-34 (Lecture Notes in Networks and Systems).

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title = "Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study: Peru During COVID-19",

abstract = "One of the main logistical problems during the COVID-19 pandemic in many countries worldwide was the movement and delivery of various medical supplies to government hospitals, including vaccines requiring special conditions for their mobilization. Many algorithmic proposals in the literature address this type of problem, such as the Capacitated Vehicle Routing Problem (CVRP), one of the most common problems that swarm intelligence algorithms address. In the present research, using graphs, an algorithmic approach based on Ant Colony Optimization (ACO) is proposed to solve the CVRP, considering constraints on both vehicle capacity and road conditions (additional information). As a case study, the logistic network established for the distribution of vaccines during the pandemic in Peru, among the different regional state hospitals, is taken directly.",

keywords = "Ant colony, Capacitated vehicle routing problem, COVID, Optimization",

author = "Luis Ramirez and Manuel Tupia and Rony Cueva",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.; 6th International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 ; Conference date: 21-10-2024 Through 25-10-2024",

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doi = "10.1007/978-3-031-98768-7\_2",

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Ramirez, L, Tupia, M & Cueva, R 2026, Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study: Peru During COVID-19. En MV Garcia, J-P Reyes, C Nuñez & C Gordón-Gallegos (eds.), Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Volume 1: Innovative Approaches in AI, IoT, and Software Systems. Lecture Notes in Networks and Systems, vol. 1516 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 17-34, 6th International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024, Ambato, Ecuador, 21/10/24. https://doi.org/10.1007/978-3-031-98768-7_2

Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study: Peru During COVID-19. / Ramirez, Luis; Tupia, Manuel ; Cueva, Rony.
Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Volume 1: Innovative Approaches in AI, IoT, and Software Systems. ed. / Marcelo V. Garcia; John-Paul Reyes; Carlos Nuñez; Carlos Gordón-Gallegos. Springer Science and Business Media Deutschland GmbH, 2026. p. 17-34 (Lecture Notes in Networks and Systems; Vol. 1516 LNNS).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study

T2 - 6th International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024

AU - Ramirez, Luis

AU - Tupia, Manuel

AU - Cueva, Rony

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

PY - 2026

Y1 - 2026

N2 - One of the main logistical problems during the COVID-19 pandemic in many countries worldwide was the movement and delivery of various medical supplies to government hospitals, including vaccines requiring special conditions for their mobilization. Many algorithmic proposals in the literature address this type of problem, such as the Capacitated Vehicle Routing Problem (CVRP), one of the most common problems that swarm intelligence algorithms address. In the present research, using graphs, an algorithmic approach based on Ant Colony Optimization (ACO) is proposed to solve the CVRP, considering constraints on both vehicle capacity and road conditions (additional information). As a case study, the logistic network established for the distribution of vaccines during the pandemic in Peru, among the different regional state hospitals, is taken directly.

AB - One of the main logistical problems during the COVID-19 pandemic in many countries worldwide was the movement and delivery of various medical supplies to government hospitals, including vaccines requiring special conditions for their mobilization. Many algorithmic proposals in the literature address this type of problem, such as the Capacitated Vehicle Routing Problem (CVRP), one of the most common problems that swarm intelligence algorithms address. In the present research, using graphs, an algorithmic approach based on Ant Colony Optimization (ACO) is proposed to solve the CVRP, considering constraints on both vehicle capacity and road conditions (additional information). As a case study, the logistic network established for the distribution of vaccines during the pandemic in Peru, among the different regional state hospitals, is taken directly.

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AN - SCOPUS:105030289749

SN - 9783031987670

T3 - Lecture Notes in Networks and Systems

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BT - Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Volume 1

A2 - Garcia, Marcelo V.

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ER -

Ramirez L, Tupia M , Cueva R. Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study: Peru During COVID-19. En Garcia MV, Reyes JP, Nuñez C, Gordón-Gallegos C, editores, Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Volume 1: Innovative Approaches in AI, IoT, and Software Systems. Springer Science and Business Media Deutschland GmbH. 2026. p. 17-34. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-98768-7_2

Ant Colony Algorithm for Supplying Medicines to Regional Hospitals in a CVRP Scenario. Case Study: Peru During COVID-19

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