Alejo-Reyes, Avelina
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Alejo-Reyes, Avelina
Alternative Name
aalejo
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ORCID
Scopus Author ID
57202425879
Researcher ID
EKT-0166-2022

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A heuristic method for the supplier selection and order quantity allocation problem

2021 , Alejo-Reyes, Avelina , Mendoza, Abraham , Olivares-Benitez, Elias

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Publication

Quadratic buck–boost converter with positive output voltage and minimum ripple point design

2018 , Rosas-caro, Julio , Jesus E. Valdez‐Resendiz , Mayo Maldonado, Jonathan , Alejo-Reyes, Avelina , Valderrabano-Gonzalez, Antonio

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Energy Recycling Laboratory Experimental Test Bench for Three-Phase FACTS Devices Prototypes

2019 , Jesus E. Valdez-Resendiz , Mayo Maldonado, Jonathan , Rosas-caro, Julio , Alejo-Reyes, Avelina , Armando Llamas-Terres , Valderrabano-Gonzalez, Antonio , Del-Valle-Soto, Carolina , Valdivia, Leonardo

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A Modified Simulated Annealing (MSA) Algorithm to Solve the Supplier Selection and Order Quantity Allocation Problem with Non-Linear Freight Rates

2023 , González Cabrera, Nora Paulina , Alejo-Reyes, Avelina , Erik Cuevas , Mendoza, Abraham

Economic Order Quantity (EOQ) is an important optimization problem for inventory management with an impact on various industries; however, their mathematical models may be complex with non-convex, non-linear, and non-differentiable objective functions. Metaheuristic algorithms have emerged as powerful tools for solving complex optimization problems (including EOQ). They are iterative search techniques that can efficiently explore large solution spaces and obtain near-optimal solutions. Simulated Annealing (SA) is a widely used metaheuristic method able to avoid local suboptimal solutions. The traditional SA algorithm is based on a single agent, which may result in a low convergence rate for complex problems. This article proposes a modified multiple-agent (population-based) adaptive SA algorithm; the adaptive algorithm imposes a slight attraction of all agents to the current best solution. As a proof of concept, the proposed algorithm was tested on a particular EOQ problem (recently studied in the literature and interesting by itself) in which the objective function is non-linear, non-convex, and non-differentiable. With these new mechanisms, the algorithm allows for the exploration of different regions of the solution space and determines the global optimum in a faster manner. The analysis showed that the proposed algorithm performed well in finding good solutions in a reasonably short amount of time.

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Inventory replenishment decisions for the supplier selection problem considering transportation freight rates and quality

2018 , Alejo-Reyes, Avelina , Mendoza, Abraham , Olivares-Benitez, Elias

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Publication

Power quality improvement by interleaving unequal switching converters

2016 , Arias-Angulo Juan Pedro , Rosas-caro, Julio , Beltran-Carbajal Francisco , Valderrabano-Gonzalez, Antonio , Haro-Sandoval, Eduardo , Gutiérrez-Alcalá, Salvador , Alejo-Reyes, Avelina , Garcia-Vite Pedro Martin

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A Mathematical Model for an Inventory Management and Order Quantity Allocation Problem with Nonlinear Quantity Discounts and Nonlinear Price-Dependent Demand

2023 , Alejo-Reyes, Avelina , Mendoza, Abraham , Erik Cuevas , Alcaraz Rivera, Miguel

This article focuses on solving the order quantity allocation problem for retailers. It considers factors such as quality constraints, nonlinear quantity discounts, and price-dependent demand. By formulating it as a nonlinear maximization problem, the article aims to find the best combination of suppliers and order quantity out of infinite solutions to maximize the retailer’s profit. The main contribution of this research is a new mathematical model that can solve the problem of quality constraint and demand in a single step. This problem is complex due to the number of equations, their nonlinear nature, and the various trade-offs given by the market. Additionally, this research considers demand as output and includes price-dependent demand, which is more realistic for retailers. The proposed model was tested using an example from the recent literature and showed better results than the previously published best solution regarding profit maximization.

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Statistical Analysis of Lean Construction Barriers to Optimize Its Implementation Using PLS-SEM and PCA

2024 , Romo Gamboa, Rubén , Alejo-Reyes, Avelina , Orozco, Francisco

The construction industry performs many tasks scheduled and related to other activities. Companies must optimize their operations, increase efficiency, eliminate waste, and deliver better products to their customers. As a result, this study aims to identify the main challenges associated with the implementation of the Lean Construction model in small and medium-sized construction companies and optimize the implementation of this process using statistically-focused mathematical models. This study was conducted using the partial least squares (PLS-SEM) method and also carried out the principal component analysis to optimize Lean barriers so that they can be properly implemented in the construction industry. The most important obstacles are displayed, as well as the relationships with other factors. Significant relationships have been discovered between the barriers to Lean construction adoption, especially with regard to corporate culture, communication, training, leadership, and the influence of mentality on business and employee adaptability. Construction executives and managers can make well-informed policy and strategic decisions by having a thorough understanding of the main barriers to Lean implementation. This information enables them to focus on the implementation of Lean technologies in projects, to increase market competitiveness, reduce waste and enhance overall work efficiency.

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An Evolutionary Algorithm-Based PWM Strategy for a Hybrid Power Converter

2020 , Rodríguez Vázquez, Alma Nayeli , Alejo-Reyes, Avelina , Erik Cuevas , Francisco Beltran-Carbajal , Rosas-caro, Julio

In the past years, the interest in direct current to direct current converters has increased because of their application in renewable energy systems. Consequently, the research community is working on improving its efficiency in providing the required voltage to electronic devices with the lowest input current ripple. Recently, a hybrid converter which combines the boost and the Cuk converter in an interleaved manner has been introduced. The converter has the advantage of providing a relatively low input current ripple by a former strategy. However, it has been proposed to operate with dependent duty cycles, limiting its capacity to further decrease the input current ripple. Independent duty cycles can significantly reduce the input current ripple if the same voltage gain is achieved by an appropriate duty cycle combination. Nevertheless, finding the optimal duty cycle combination is not an easy task. Therefore, this article proposes a new pulse-width-modulation strategy for the hybrid interleaved boost-Cuk converter. The strategy includes the development of a novel mathematical model to describe the relationship between independent duty cycles and the input current ripple. The model is introduced to minimize the input current ripple by finding the optimal duty cycle combination using the differential evolution algorithm. It is shown that the proposed method further reduces the input current ripple for an operating range. Compared to the former strategy, the proposed method provides a more balanced power-sharing among converters.

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Publication

Optimal Selection of Capacitors for a Low Energy Storage Quadratic Boost Converter (LES-QBC)

2023 , Jose Solis-Rodriguez , Rosas-caro, Julio , Alejo-Reyes, Avelina , Jesus E. Valdez-Resendiz

This article studies a recently proposed dc-dc converter and its optimization in terms of capacitors selection through the Particle Swarm Optimization (PSO) algorithm. The converter under study is the so-called Low Energy Storage Quadratic Boost Converter (LES-QBC), a quadratic type of converter that offers a smaller Output Voltage Ripple (OVR) compared to the traditional quadratic boost topology with capacitors of the same characteristics. This study presents a way to select the capacitors for minimizing the OVR while achieving a constraint of a maximum stored energy in capacitors. The capacitor’s stored energy is given as a design specification. The results are compared against the traditional quadratic boost converter and the LES-QBC without optimization (equal capacitance in capacitors). The optimization algorithm used was the so-called Particle Swarm Optimization (PSO). The experimental results demonstrate the effectiveness of the proposition. For the design exercise used for the results, the capacitor’s stored energy was kept almost the same, and a reduction in the OVR was achieved versus the non-optimized LES-QBC.

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