Rodríguez Aguilar, Román
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Rodríguez Aguilar, Román
Official Name
Rodríguez Aguilar, Román
Alternative Name
Rodríguez-Aguilar, Román
Rodríguez-Aguilar, R.
Aguilar, R.R.
Rodriguez-Aguiler, R.
Rodríguez, R.
Roman, R.A.
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ORCID
Scopus Author ID
56717663000
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AAO-6158-2020

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An Asset Index Proposal for Households in Mexico Applying the Mixed Principal Components Analysis Methodology

2021 , Rodríguez Aguilar, Román , DelaTorre-Diaz, Lorena

The development of assets indices has grown as an alternative to measure wealth from different generations in the evaluation of social mobility. A proposal of the development of an asset index is presented using the GSVD-based mixed principal components analysis (PCAMix package in R). The contribution rests in the combination of both numerical and categorical data and the integration of the simultaneous effect of these variables in the index. It was used in profiling the Mexican households according to the information from the 2018 National Household Income and Expenditure and the determination of the Gini coefficient to evaluate the inequality of distribution at the state level. Results show a high level of disparity in the distribution of assets with only 0.01% of the households possessing 40% or more of the assets included in the index, being the southern region where greatest challenges for ascending social mobility.© Springer Nature

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Impuestos en botanas. Su impacto en precio y consumo en México

2017 , Aguilera Aburto, Nelly , Rodríguez Aguilar, Román , Sansores Martínez, Diana Nicte-Há , Gutiérrez Delgado, Cristina

Antecedentes: Para contribuir al control de la epidemia de sobrepeso y obesidad en México, se implementó, a partir de enero de 2014, una estrategia integral que incluye un impuesto a bebidas azucaradas y a un grupo de alimentos con alto contenido calórico, entre los que se encuentran las botanas. En este artículo analizamos cómo se comportan los precios de las botanas ante el incremento de los impuestos y estimamos el posible impacto del incremento en precios en el consumo.Métodos: Para el análisis de precios aplicamos un modelo de datos panel con tres escenarios y un modelo de series de tiempo interrumpidas. Para la estimación del posible impacto del incremento en precios en el consumo desarrollamos escenarios de elasticidad y tasas de impuesto. En ambos casos usamos información pública del INEGI.Resultados: Del análisis de precios, los resultados indican que la industria transfirió el impuesto al precio en las botanas en su totalidad. Asimismo muestran que el impuesto vigente de 2014 a 2016 generó una disminución moderada del consumo. Las estimaciones del impacto en el consumo indican que una mayor tasa impositiva generaría mayores disminuciones de consumo y que la medida impositiva sería más efectiva si las demandas son elásticas.Conclusiones: Los resultados proporcionan información para replantear el nivel de tasa impositiva y alertar sobre la necesidad de evaluar la estrategia en su conjunto. ©2017 Fondo de Cultura Económica, Los autores.

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Preface: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023) : Volume 4

2023 , Vasant, Pandian , Weber, Gerhard-Wilhelm , Arefin, Mohammad Shamsul , Rodríguez Aguilar, Román , Panchenko, Vladimir , Munapo, Elias , Thomas, Joshua , Pandian Vasant , Mohammad Shamsul Arefin , Vladimir Panchenko , J. Joshua Thomas , Elias Munapo , Gerhard-Wilhelm Weber , Roman Rodriguez-Aguilar

The sixth edition of the International Conference on Intelligent Computing and Optimization (ICO’2023) was held during April 27–28, 2023, at G Hua Hin Resort and Mall, Hua Hin, Thailand. The objective of the international conference is to bring the global research scholars, experts and scientists in the research areas of intelligent computing and optimization from all over theworld to share their knowledge and experiences on the current research achievements in these fields. This conference provides a golden opportunity for global research community to interact and share their novel research results, findings and innovative discoveries among their colleagues and friends. The proceedings of ICO’2023 is published by SPRINGER (in the book series Lecture Notes in Networks and Systems) and indexed by SCOPUS. ©2023 Springer, ©2023 The authors.

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Quantum-behaved bat algorithm for solving the economic load dispatch problem considering a valve-point effect

2020 , Vasant, Pandian , Parvez Mahdi, Fahad , Marmolejo Saucedo, José Antonio , Litvinchev, Igor , Rodríguez Aguilar, Román , Watada, Junzo

Quantum computing-inspired metaheuristic algorithms have emerged as a powerful computational tool to solve nonlinear optimization problems. In this paper, a quantum-behaved bat algorithm (QBA) is implemented to solve a nonlinear economic load dispatch (ELD) problem. The objective of ELD is to find an optimal combination of power generating units in order to minimize total fuel cost of the system, while satisfying all other constraints. To make the system more applicable to the real-world problem, a valve-point effect is considered here with the ELD problem. QBA is applied in 3-unit, 10-unit, and 40-unit power generation systems for different load demands. The obtained result is then presented and compared with some well-known methods from the literature such as different versions of evolutionary programming (EP) and particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE), simulated annealing (SA) and hybrid ABC_PSO. The comparison of results shows that QBA performs better than the above-mentioned methods in terms of solution quality, convergence characteristics and computational efficiency. Thus, QBA proves to be an effective and a robust technique to solve such nonlinear optimization problem.

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Machine learning models in health prevention and promotion and labor productivity: A co-word analysis

2024 , Sergio Arturo Dominguez Miranda , Rodríguez Aguilar, Román

Objective: The objective of this article is to carry out a co-word study on the application of machine learning models in health prevention and promotion, and its effect on labor productivity. Methodology: The analysis of the relevant literature on the proposed topic, identified in the last 15 years in Scopus, is considered. Articles, books, book chapters, editorials, conference papers and reviews refereed publications were considered. A thematic mapping analysis was performed using factor analysis and strategy diagrams to derive primary research approaches and identify frequent themes as well as thematic evolution. Results: The results of this study show the selection of 87 relevant publications with an average annual growth rate of 23.25% in related production. The main machine learning algorithms used, the main research approaches and key authors, derived from the analysis of thematic maps, were identified. Conclusions: This study emphasizes the importance of using co-word analysis to understand trends in research on the impact of health prevention and promotion on labor productivity. The potential benefits of using machine learning models to address this issue are highlighted and anticipated to guide future research focused on improvements in labor productivity through prevention and promotion of health. Originality: The identification of the relationship between work productivity and health prevention and promotion through machine learning models is a relevant topic but little analyzed in recent literature. The analysis of co-words allows us to establish the reference point of the state of the art in this regard and future trends.

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Household Expenditure in Health in Mexico, 2016

2019 , Rodríguez Aguilar, Román , Ramírez Pérez, Héctor Xavier

The aim of this research is to evaluate the financial protection of public health insurance by analyzing the percentage of households with catastrophic expenditure in health (HCEH) in Mexico and its relationship with the condition of poverty, the state, the condition of insurance, and the items of health expenditure. A special emphasis was placed on the poorest households (income quintile I). Method: The National Household Income and Expenditure Survey 2002–2016 was used to estimate the percentage of HCEH. The analysis was carried out with Stata-SE 12. Results: in 2016 there was 2.13% of HCEH (1.82–2.34%, N = 657,474). Conclusions: the percentage of HCEH decreased in recent years, although in 2016 it increased slightly, improving financial protection in health. This decrease seems to have stagnated, maintaining inequities in access to health services, especially in the rural population without affiliation to any health institution. © 2020, Springer Nature Switzerland AG.

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Proposal for a comprehensive environmental key performance index of the green supply chain

2020 , Rodríguez Aguilar, Román

The consideration of environmental objectives in the design of green supply chains creates the need to build a set of key performance indicators for monitoring and control. There is a set of generally accepted environmental indicators for monitoring environmental objectives in the supply chain. However, so far these indicators have been disconnected from the operational and economic indicators of the supply chain. It is important to consider these elements in the integral performance of a green supply chain. The present work is a proposal of a general index of environmental performance that includes operational, financial, and environmental aspects that allow monitoring the integral performance of the supply chain by applying Principal Component Analysis of mixed data. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

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The mahalanobis distance between the hurst coefficient and the Alpha-Stable parameter: An early warning indicator of crises

2016 , Rodríguez Aguilar, Román , Cruz-Aké, Salvador , Venegas-Martínez, Francisco

The Hurst coefficient and the alpha-stable parameter are useful indicators in the analysis of time series to detect normality and absence of self-similarity. In particular, when these two features met simultaneously the series is driven by white noise. This paper is aimed at developing an index to measure the degree to which a time series departs from white noise. The proposed index is built by using the principal component analysis of the Mahalanobis distances between the Hurst coefficient and the alpha-stable parameter from theoretical values of normality and absence of self-similarity. The proposed index is applied to examine the Mexican Peso exchange rate against the US Dollar. The distinctive characteristic of the index is that it can be used as an early warning indicator of crises, as it is shown for the Mexican case. © 2010, Academic Publications, Ltd.; https://ijpam.eu ©The authors.

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Catastrophic Health Spending by COVID-19 in the Mexican Insurance Sector

2024-01-01 , Domínguez-Gutiérrez, Ulises , Rodríguez Aguilar, Román

The COVID-19 pandemic that the world has been suffering for 3 years has generated major impacts worldwide, both in public health systems and in the private insurance industry. The high costs of care derived from cases with complications have likewise generated a great impact on the private insurance industry. In the case of Mexico, the mortality rates observed are among the first places, in addition to generating a great impact on private insurance. This work deals with the measurement of the impact of catastrophic expenses derived from COVID-19 in an insurance company; using a set of machine learning models, the key variables in the estimation of patients with potential catastrophic expenses were determined. The results show that the estimated classification model has a positive performance in addition to allowing the identification of the main risk factors of the insured as well as their potentially catastrophic impact on insurance companies.© 2024 Springer Nature

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A Timetabling Application for the Assignment of School Classrooms

2019 , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

In this manuscript a group of students from an university of Mexico develop a user-friendly university timetabling tool based on a spreadsheet and using Open-Solve optimization software. The developed tool uses 0–1 integer programming to maximize the number of classes with their respective teacher allocated to a classroom in a certain time schedule. It does not solve only one specific case, the user can introduce each semester’s specific information to the spreadsheet and the tool will automatically generate a schedule that maximizes the number of classes assigned using the given time and classroom resources. Each semester the available times and the teacher can be changed for each class according to the needs for that specific semester. The user does not need to be someone who understands linear programming. The tool is developed on a user-friendly way so that the staff of the school can use it without help from the developers. In this paper we will show how this tool was developed for a smaller example and how it works with a real case. © 2020, Springer Nature Switzerland AG.

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