COVID-19 Vaccine’s distribution routes with bioinspired metaheuristic algorithms: Resoluteness

Authors

  • Leonardo Daniel Estrada Moreno Universidad Autónoma del Estado de México
  • Rosa María Valdovinos Rosas Universidad Autónoma del Estado de México
  • Lourdes Loza Hernandez Universidad Autónoma del Estado de México https://orcid.org/0000-0001-5107-7110
  • Roberto Alejo Tecnológico Nacional de Mexico / IT Toluca https://orcid.org/0000-0002-7580-3305

Keywords:

Artificial Bee Colony Algorithm, Bio-inspired, Capacitated Vehicle Routing Problem, Genetic Algorithm, Metaheuristics, Particle Swarm Optimization Algorithm

Abstract

The global emergency of COVID-19 caused by the SARS-CoV-2 virus at the end of 2019, was without a doubt a critical and historical point for society in general; for instance, the effective development of vaccines, as well as the efficient distribution of them; They were an unprecedented challenge to slow down the spread or mitigate its impact on societies around the world. This article specifies three bio-inspired metaheuristic algorithms (genetic algorithm, particle swarm optimization algorithm, and artificial bee colony algorithm) that were used in the context of the capacitated vehicle routing problem to generate vaccine distribution routes, specifically, COVID-19 vaccine for over 18 years old the first and the second doses applications in Mexico, particularly in the State of Mexico. The quality of the solutions obtained by these algorithms is compared, as a result of the performance of the particle swarm optimization (PSO) algorithm being superior in solution quality.

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Author Biographies

Leonardo Daniel Estrada Moreno, Universidad Autónoma del Estado de México

Leanoardo Estrada is a Computer Engineer from the Faculty of Engineering at the Universidad Autónoma del Estado de México (UAEM). Engaged in research projects related to data processing, data science, and analytics applied to real-world problems.

Rosa María Valdovinos Rosas, Universidad Autónoma del Estado de México

Rosa Valdovinos has Ph.D. in Computer Sciences and is a member of the National Researchers System at level II. Her work has contributed to various PRONACES (National Programs for Scientific Research and Technological Development), including research projects, articles in indexed journals and conferences, book chapters, books, and one patented license. She has mentored students at the undergraduate, master's, and doctoral levels. Actively involved in organizing academic events to promote science, she also focuses on initiatives targeting girls in computing and fostering early vocations. With over 1000 citations and an H14 index, the International AD Scientific Index 2023 recognizes her as one of the 10,000 most influential scientists at the national level.

Lourdes Loza Hernandez, Universidad Autónoma del Estado de México

Lourdes Loza got her degree in Computer Engineering at the Universidad Autónoma del Estado de México (UAEM). She finished a Ph.D. in Industrial Engineering in Supply Chain at the Instituto Tecnológico de Monterrey, México, with an internship at the Research Center CIRRELT of Montreal, Canada. College, master, and Ph.D. degrees are certificated by Toronto University, Canada. Her research interests are Risk Assessment, Supply Chain, and Reverse Logistics. She has published in the International Journal of Disaster Risk Reduction, Structure and Infrastructure Engineering, Journal of Business Process Management, and International Journal of Applied Management Science. She belows to the National Researchers System (SNI-I)

Roberto Alejo, Tecnológico Nacional de Mexico / IT Toluca

Roberto Alejo has Ph.D. in Advanced Computer Systems from the Universitat Jaume I (Spain), and he is affiliated with the Technological Institute of Toluca, National Technological Institute of Mexico, with a profound scientific interest in the application of artificial intelligence to the solution of real-world problems. Additionally, he is a specialist in artificial neural networks, machine learning, and data mining.

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Published

2024-05-15

How to Cite

Estrada Moreno, L. D., Valdovinos Rosas, R. M. ., Loza Hernandez, L., & Alejo, R. (2024). COVID-19 Vaccine’s distribution routes with bioinspired metaheuristic algorithms: Resoluteness. IEEE Latin America Transactions, 22(6), 484–493. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/8709

Issue

Vol. 22 No. 6 (2024): Ordinary Issue

Section

Computing