Rodríguez Aguilar, Román
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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 17
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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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Digital Twins and Blockchain: Empowering the Supply Chain

2022 , Aguilar Ramírez, José Eduardo , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

Industry 4.0 is here, and it arrived with very promising new technologies that can foster he supply chain management across industries. In this paper we review multiple sources to identify the main characteristics of Digital Twins and Blockchain technologies and how they can work together to fulfill the needs of the supply chain. We identify some advantages and disadvantages that must be properly analyzed before adopting this approach into any business. Many applications behind these new benefits are still in development, but we believe these two technologies have great potential. © Springer Nature

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Backbone Distribution Network Design for the Mexican Automotive Industry

2020 , Retana-Blanco, Brenda , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román , Pedraza-Arroyo, Erika

The logistics network of an automotive company in Mexico was analyzed to propose a better logistics network in the country to improve delivery times to customers. The analysis was conducted with Greenfield Analysis and Network Optimization. Taking into account the information given by the company, it was possible to obtain optimal scenarios for better operation, which involved the construction of distribution centers in the Hidalgo state in Mexico. © Springer Nature Switzerland AG 2020.

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The supply chain event management application: a case study

2019 , Palma, Fanny , Saucedo, Jania A. , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

A deviation from planned processes reveals the consequences that a disruption can cause in any area, even more a disruption with Ripple Effect (RE), which implied for the global Supply Chain (SC) when depends essentially from the stakeholders in all levels and chains. The learnt lessons from these tragical events show that many companies could not assess the impact and its side effects, therefore they cannot respond adequately, prolonging the crisis and expanding the disruption. A disruption evaluation model would allow to know from the beginning the potential impact to check carefully into the critical events to provide the necessary resources to control it. Hence, it is relevant that SC managers know and employ the right tools to focus on the control and the solution; as well to evaluate the impact and the disruption criticality level to mitigate and control the impact with total certainty that the appropriate actions are being taken according to the problematic. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

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Key Factors in the Successful Integration of the Circular Economy Approach in the Industry of Non-durable Goods: A Literature Review

2022 , Jacinto-Cruz, Marcos , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio

Nowadays consumers are more informed about the characteristics of the products they are buying and the services they are using as well as their respective environmental impacts. The nondurable goods industry is the closest to consumers in everyday life, therefore awareness of the environmental impacts of these products has gained greater attention from consumers. In response to increased consumer demand for environmental attributes, the nondurable goods industry has begun to apply circular economy guidelines in its supply chain, in addition to complying with new environmental regulations in various countries. This research addresses a literature review to identify the key factors that allow the correct implementation of the circular economy approach in the non-durable goods industry. Among the main factors identified are the voice of the customer, the traceability and collection of empty containers, as well as and efficient international environmental regulation. © Springer Nature

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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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Statistical Learning Applied to Malware Detection

2020 , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio

This work shows an application of statistical learning methodologies in order to determine the important factors for malware detection. Support Vector Machines and Lasso Regression performed Malware classification with additional re-sampling methods. The results show that the Lasso Regression allows an efficient selection of relevant variables for the construction of the classifier, also the integration of support vector machines improves the efficiency of the classifier through the application of resampling methods. The model presented in this paper uses a statistical learning approach through the selection of variables, non-linear classification, and resampling methods. © 2020, Springer Nature Switzerland AG.

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Estimation of the Stochastic Volatility of Oil Prices of the Mexican Basket: An Application of Boosting Monte Carlo Markov Chain Estimation

2021 , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

The volatility of the returns on financial assets is not a constant number over time as many valuation models, mainly derivatives, developed during the 80's, assume. The complexity of non-heteroscedasticity and the difference in results when estimated with different methodologies such as historical, implicit or stochastic calculation, make this subject too extensive a field to be covered in this work. However, stochastic volatility has been widely accepted in recent years. Monte Carlo Markov Chain (MCMC) method is explained and used to estimate the distribution of oil prices of Mexican basket as a stochastic variable. MCMC in the univariate case, supposes that we can estimate the distribution of a latent (hidden) variable through the behavior of another variable observed posteriori with the help of Bayesian inference; this method allows an efficient inference independent of the underlying process through an algorithm. The results show a correct adjustment of stochastic volatility to the behavior of the oil prices. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Estimation of Electricity Prices in the Mexican Market

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

This paper presents an alpha stable regression model to estimate prices in the Mexican Electric Market. This market began operations in February 2016. The observed prices show great fluctuations in the observed data due to diverse aspects, a seasonality of the demand, the availability of fuel and the problems of congestion in the electrical network. 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 of the 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. © 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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