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A machine learning-based analytical intelligence system for forecasting demand of new products based on chlorophyll : a hybrid approach

2024 , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio , Garcia-Llamas, Eduardo , Rodríguez-Aguilar, Miriam , Marmolejo-Saucedo, Liliana

This manuscript addresses the problem of forecasting the demand for innovative products with limited and inhomogeneous sales data over time. The main objective of the study is to use the information available from a group of innovative chlorophyll-based food products to build a coherent demand forecasting system. From a transactional database, time series were constructed for each group of products, analyzing the stationarity and seasonality of the time series through the Dickey–Fuller and Canova–Hansen tests. Likewise, an ARIMA model, a long short-term memory (LSTM) recurrent deep neural network, and a support vector machine (SVM) were trained to select the best model for each product based on a forecast performance metric. A comparison between classical forecasting techniques and machine learning models is shown. The LSTM neural network was the best model for most products because the internal architecture of the network allows not only to capture non-linear relationships between variables but is also capable of controlling the flow of information to preserve characteristics over time that are relevant for forecasts. The second-best model was the SVM, which allows capturing non-linear behaviors through kernel functions and uses a smaller amount of data for its estimation. Finally, the ARIMA model presented the lowest performance for all products. The objective of having various methodologies is that the system allows the best forecast to be selected according to the type of product, availability of information and methodology used, which will allow the company to integrate new products into the system over time. ©Springer

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Conceptual framework of Digital Health Public Emergency System: digital twins and multiparadigm simulation

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

Introduction: Two major technological paradigms have been developed in recent years, digital twins and the multiparadigm simulation. In the Health Sector, the enormous potential of both approaches for the management of public health emergencies is envisioned. Objectives: This study aims to develop the conceptual framework for the development of a Digital Public Health Emergency System. Methods: The integration of the digital twins in health with the multi-paradigm simulation for the design of a digital system of public health emergencies is proposed.

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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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Liberalization of the Mexican Electricity Sector: A Study of Technical Efficiency

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

This article discusses the recent reform implemented in the Mexican electricity sector. As part of the structural reforms carried out in Mexico during the last 6 years (2012–2018), the opening of this sector to foreign capital, the creation of a wholesale electricity market, and the end of the monopoly of a CFE (Federal Electricity Commission, a government company) are the main changes. This study addresses an estimation of technical efficiency of power thermal units within the framework of the liberalization of the Mexican electricity market. These estimations are relevant because a single supplier, even before liberalization, must form a portfolio of the most efficient plants to be able to compete in the electricity market. The main results show the composition of a set of power thermal plants that are the most efficient of the total number of plants in operation and that could represent CFE in the wholesale electricity market. © Springer Nature Switzerland AG 2019.

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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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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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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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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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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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A brief literature review of quantitative models for sustainable supply chain management

2022 , Flores-Sigüenza, Pablo , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

Supply chain management is the basis for the execution of operations, being considered as the core of the business function in the 21st century. On the other hand, at present, factors such as the reduction of natural resources, the search for competitive advantages, government laws, and global agreements have generated a greater interest in the sustainable development, which, in order to achieve it, industries need to rethink and plan their supply chain considering a path of sustainability. So sustainable supply chain management emerges as a means to integrate stakeholders' concern for profit and cost reduction with environmental and social requirements, attracting significant interest among managers, researchers, and practitioners. The main objective of this study is to provide a synthesis of the key elements of the quantitative model offerings that use sustainability indicators in the design and management of forward supply chains. To achieve this objective, we developed a systematic literature review that includes 80 articles published during the last decade in peer-reviewed journals in English language. In addition, a 4W's analysis (when, who, what, and where) is applied and three structural dimensions are defined and grouped by categories: supply chain management, modeling, and sustainability. As part of the results, we evidenced a continuous growth in the scientific production of this type of articles, with a predominance of deterministic mathematical programming models with an environmental economic perspective. Finally, we identified research gaps, highlighting the lack of integral inclusion of a life cycle analysis in the design of supply chain networks. © 2022 Elsevier Inc. All rights reserved.