Rodríguez Aguilar, Román
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Preferred name
Rodríguez Aguilar, Román
Official Name
Rodríguez Aguilar, Román
Alternative Name
rrodrigueza
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ORCID
Scopus Author ID
56717663000
Researcher ID
AAO-6158-2020

Research Output
Now showing 1 - 10 of 52
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Prices of Mexican Wholesale Electricity Market: An Application of Alpha-Stable Regression

2019 , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio , Brenda Retana-Blanco

This paper presents a proposal to estimate prices in the Mexican Wholesale Electric Market, which began operations in February 2016, which is why it moves from a scheme with a single bidder to a competitive market. There are particularities in the case of the Mexican market, the main one being the gradual increase in the number of competitors observed until now and, on the other hand, the geographic and technical characteristics of the electric power generation. The observed prices to date show great fluctuations in the observed data due to diverse aspects; among the stems we can mention the own seasonality of the demand of electrical energy, the availability of fuel, the problems of congestion in the electrical network, as well as other risks such as natural hazards. For the above, it is relevant in a market context to have a price estimation as accurate as possible for the decision-making of supply and demand. This paper proposes a methodology for the generation of electricity price estimation through the application of stable alpha regressions, since the behavior of the electric market has shown the presence of heavy tails in its price distribution. © 2019 by the authors, Sustainability.

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Structural Dynamics and disruption events in Supply Chains using Fat Tail Distributions

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

The analysis of structural dynamics in a supply chain requires robust methods for the modeling of disruption events that can be faced. Statistical modeling, the machine learning application and access to large amounts of data require much more realistic models to manage risk in the supply chain. This study proposes a statistical methodology for the modeling of disruption events in the supply chain with heavy tailed distributions, which will allow the construction of models more closely linked to reality for risk management in the supply chain. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

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Modeling the Optimal Supply Chain of Liquefied Natural Gas as Fuel in Fishing Vessels in Mexico

2022 , Hernández-Palomo, Giovanna , Rodríguez Aguilar, Román , Venegas-Martínez, Francisco

The global energy transition process has generated a set of modifications in the generation and consumption of energy. Environmental objectives have gained great relevance for regions, countries and companies. The fishing sector has been identified as having a broad environmental impact, which is why the transition to cleaner energy sources in this sector has been considered. One of the proposed strategies is based on the transition from the diesel engines of the ships to the use of liquefied natural gas (LNG), however, this transition requires guaranteeing the supply of fuel as well as the process of reconversion of units in operation and the impulse of LNG gas engines for new units. This work presents a proposal for the design of an LNG gas supply chain for the fishing industry in the State of Tampico in Mexico that allows evaluating the feasibility of the transition from the use of diesel to natural gas in fishing vessels. The main results show the feasibility of the transition in the fuel supply and economic and environmental benefits for the fishing industry. However, there is a significant challenge in converting units in operation to the use of natural gas due to the lack of public policies that promote and support its use in this sector. © Mobile Networks and Applications

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A Hybrid Model for Improving the Performance of Basketball Lineups

2020 , Rodríguez Aguilar, Román , Infante-Escudero, Rodrigo , Marmolejo Saucedo, José Antonio

An optimization model of the NBA team lineups is presented to improve the performance of the teams according to the selected lineup. A set of variables such as inputs and outcome variables are taken into account to optimize the results. Additionally, a technical efficiency analysis was performed on the performance of the lineups selected by the optimization model to validate the results. The results show that the lineups selected through the optimization model were those with greater technical efficiency for the equipment. The application of optimization methods and technical efficiency can be a robust tool for decision making in the sports field. © Springer Nature Switzerland AG 2020.

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Dynamics of prices and consumption of unhealthy foods as a monitoring tool of the strategy against obesity in Mexico

2020 , Lozano-Díez, José Antonio , Rodríguez Aguilar, Román

Introduction: Mexico faces an epidemic of overweight and obesity, in 2018 75% of adults were overweight or obese. This condition as a risk factor generates a significant financial impact in the Health Sector. In response, the National Strategy for Prevention and Control of Overweight, Obesity, and Diabetes was implemented in 2013, which included as one of its pillars the implementation of fiscal policies. As part of fiscal policy, taxes were established on sugary drinks and foods with high-calorie content. Seven years after the implementation of the Strategy to control the epidemic of overweight and obesity, there have been some results. However, it is necessary to continue working and especially monitoring the performance of the different actions implemented. Objectives: Propose an analytical intelligence model for monitoring the fiscal policies implemented to control overweight and obesity in Mexico. Methods: The proposed analytical intelligence model considers three methodological bases, a) price index of healthy and unhealthy foods through Principal Component Analysis, b) volatility measurement of both baskets through a GARCH model and c) monitoring of consumption patterns through household income and expenditure surveys. Results: The main results identified a price differential between the baskets of products healthy and unhealthy, especially at the beginning of the fiscal policy. Healthy products have higher price volatility than unhealthy products and according to consumption patterns, on average Mexican households spend 30% of their food expenditure on unhealthy products. Conclusion: To strengthen fiscal actions to control overweight and obesity, it is recommended to have monitoring systems for the dynamic design and implementation of public policies. Although taxes have reduced in some grade the consumption of unhealthy products, it is necessary to promote the affordability of healthy products, helping to improve the diet of Mexican households. © 2019 José Antonio Lozano Díez & Roman Rodríguez Aguilar, licensed to European Alliance for Innovation.

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An analytical intelligence model for the management of resources for the treatment of high-cost diseases: the case of HIV in Mexico

2020 , Rodríguez Aguilar, Román , Rivera-Peña, Gustavo

In the health sector, it is very important to have adequate control over the allocation of resources; this becomes much more relevant in the case of high-cost diseases, HIV is one example of this. The use of analytical intelligence allows the transformation of raw data into meaningful and useful information to make decisions. To support the management of resources in the health sector an analytical intelligence model based on survival analysis of patients under antiretroviral treatment in the Ministry of Health of Mexico is proposed. A survival model was carried out using a cohort of people with HIV under antiretroviral treatment attended by the Ministry of Health for the period 2007–2015. Sociodemographic variables, viral load, dates of treatment initiation and death were used. Kaplan–Meier method and the logarithmic rank test, as well as the Cox proportional-hazard model, were used. The proposed model can serve as a strategic information management tool for decision-making about the care and financing of high-cost diseases in the health sector. The results show that the probability of survival in people with HIV is higher for currently preferred treatments for treatment initiation and recently incorporated. Increasing the level of CD4 for the start of treatment generates greater probabilities of survival for patients. It is necessary to comprehensively evaluate the prescription and initiation of treatment policies according to CD4 levels to guarantee the financial sustainability of antiretroviral treatment in the Ministry of Health since these measures imply greater use of resources. It would be helpful to implement this type of analytical intelligence model for the monitoring and management of resources in the health sector. © Springer Nature

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Electric Vehicles as Distributed Micro Generation Using Smart Grid for Decision Making: Brief Literature Review

2022 , Sanchez-García, Julieta , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio

This article deals with a brief review of the literature about the potential use of renewable energies through the integration of smart grids and the use of electric vehicles as micro generators that allow energy exchange with the grid. The main technical aspects are addressed, as well as potential benefits and requirements necessary for said integration. Highlighting key aspects in the integration of smart grids, energy storage systems, prosumers and their interaction with electrical vehicles on the grid. © Springer Nature

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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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Selecting the Distribution System using AHP and Fuzzy AHP Methods

2024 , Saucedo-Martínez, Jania Astrid , Salais-Fierro, Tomás Eloy , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio

In this research, we present a supporting tool for decision making by designing a distribution system for a trading company of supplies for the welding industry in Mexico. The case study encompasses a distribution system with shortage problems and poor fleet capacity. To address these problems, improvement options were grouped into three possible scenarios through a third-party logistics (3PL) service. Furthermore, for the evaluation and selection of one of the scenarios, the Analytic Hierarchy Process (AHP) methodology was proposed integrating fuzzy logic as a tool for decision making, including factors of uncertainty and subjectivity as well as a comparison with traditional AHP obtaining the best scenario, meeting the requirements of the company, and showing potential improvements in the desired service level for its distribution system. © 2024 Springer Nature

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Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle

2019 , Vasant, Pandian , Marmolejo Saucedo, José Antonio , Litvinchev, Igor , Rodríguez Aguilar, Román

Currently, there is a remarkable focus on green technologies for taking steps towards more use of renewable energy sources within the sector of transportation and also decreasing pollution. At this point, employment of plug-in hybrid electric vehicles (PHEVs) needs sufficient charging allocation strategy, by running smart charging infrastructures and smart grid systems. In order to daily usage of PHEVs, daytime charging stations are required and at this point, only an appropriate charging control and a management of the infrastructure can lead to wider employment of PHEVs. In this study, four swarm intelligence based optimization techniques: particle swarm optimization (PSO), gravitational search algorithm (GSA), accelerated particle swarm optimization, and hybrid version of PSO and GSA (PSOGSA) have been applied for the state-of-charge optimization of PHEVs. In this research, hybrid PSOGSA has performed very well in producing better results than other stand-alone optimization techniques. © 2021 Springer Nature Switzerland AG. Part of Springer Nature.

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