Mendoza, Abraham
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Preferred name
Mendoza, Abraham
Official Name
Mendoza Andrade, Abraham
Alternative Name
amendoza
Main Affiliation
ORCID
Scopus Author ID
56002690300
Researcher ID
V-4102-2018

Research Output
Now showing 1 - 10 of 30
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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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CAR: heuristics for the inventory routing problem

2020 , Ramkumar Nambirajan , Mendoza, Abraham , Subramanian Pazhani , T. T. Narendran , K. Ganesh

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Inventory replenishment decisions model for the supplier selection problem facing low perfect rate situations

2019 , Alejo-Reyes, Avelina , Mendoza, Abraham , Olivares-Benitez, Elias

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An application of interactive fuzzy optimization model for redesigning supply chain for resilience

2022 , Kanokporn Kungwalsong , Mendoza, Abraham , Vasanth Kamath , Subramanian Pazhani , Marmolejo Saucedo, José Antonio

AbstractSupply chain disruptions compel professionals all over the world to consider alternate strategies for addressing these issues and remaining profitable in the future. In this study, we considered a four-stage global supply chain and designed the network with the objectives of maximizing profit and minimizing disruption risk. We quantified and modeled disruption risk as a function of the geographic diversification of facilities called supply density (evaluated based on the interstage distance between nodes) to mitigate the risk caused by disruptions. Furthermore, we developed a bi-criteria mixed-integer linear programming model for designing the supply chain in order to maximize profit and supply density. We propose an interactive fuzzy optimization algorithm that generates efficient frontiers by systematically taking decision-maker inputs and solves the bi-criteria model problem in the context of a realistic example. We also conducted disruption analysis using a discrete set of disruption scenarios to determine the advantages of the network design from the bi-criteria model over the traditional profit maximization model. Our study demonstrates that the network design from the bi-criteria model has a 2% higher expected profit and a 2.2% lower profit variance under disruption than the traditional profit maximization solution. We envisage that this model will help firms evaluate the trade-offs between mitigation benefits and mitigation costs.

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Collection of Solid Waste in Municipal Areas: Urban Logistics

2019 , Jania Astrid Saucedo Martinez , Mendoza, Abraham , Maria del Rosario Alvarado Vazquez

A sustainable process satisfies the current needs without compromising the ability of future generations to satisfy their own needs; that is, it must have a triple impact (sustainability): social, economic, and environmental. In México, there are several services that the government must provide to society for its proper development, for example, the collection of solid waste. Urban logistics include all the processes and operations that provide a service to the community, such as water, safety, health, waste collection, etc., providing the service with the lowest possible cost (economic, social, and environmental) that contributes to the sustainability of the city. Due to the accelerated growth of the world population, several environmental problems have arisen, among them, the generation of solid waste in important quantities; their proper management is relevant for adequate development of the population. The collection of solid waste in municipal areas aims to grant green spaces and recreation areas for the citizens. Although an outstanding effort has been made by the government to provide an adequate service, there are still gaps in the application of correct tools that guarantee efficiency in operations and continuity in services. This article presents a proposal to improve the planning of the design of territories for the cleaning, weeding, and collection of solid waste in municipal areas, using two MILP (Mixed Integer Linear Programming) models. The main contribution of the adaptation of this model is the application to the weeding and waste collection service municipality of the Monterrey Metropolitan Area, which considers important factors among which are the amount of waste, frequency, and service coverage.

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Modeling actual transportation costs in supplier selection and order quantity allocation decisions

2011 , Mendoza, Abraham , José A. Ventura

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EOQ Models with Two Modes of Freight Transportation and All-Units Quantity Discounts

2013 , Mendoza, Abraham , José A. Ventura

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Differential Evolution Based Algorithm for Optimal Current Ripple Cancelation in an Unequal Interleaved Power Converter

2021 , Rosas-caro, Julio , Pedro M. García-Vite , Rodríguez Vázquez, Alma Nayeli , Mendoza, Abraham , Alejo-Reyes, Avelina , Erik Cuevas , Francisco Beltran-Carbajal

This paper proposes an optimal methodology based on the Differential Evolution algorithm for obtaining the set of duty cycles of a recently proposed power electronics converter with input current ripple cancelation capability. The converter understudy was recently introduced to the state-of-the-art as the interleaved connection of two unequal converters to achieve low input current ripple. A latter contribution proposed a so-called proportional strategy. The strategy can be described as the equations to relate the duty cycles of the unequal power stages. This article proposes a third switching strategy that provides a lower input current ripple than the proportional strategy. This is made by considering duty cycles independently of each other instead of proportionally. The proposed method uses the Differential Evolution algorithm to determine the optimal switching pattern that allows high quality at the input current side, given the reactive components, the switching frequency, and power levels. The mathematical model of the converter is analyzed, and thus, the decision variables and the optimization problem are well set. The proposed methodology is validated through numerical experimentation, which shows that the proposed method achieves lower input current ripples than the proportional strategy.

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Multi-period multi-product closed loop supply chain network design: A relaxation approach

2021 , Subramanian Pazhani , Mendoza, Abraham , Ramkumar Nambirajan , T.T. Narendran , K. Ganesh , Olivares-Benitez, Elias

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Numerical Optimization of the Capacitors Selection in the MSBA Converter to Reduce the Output Voltage Ripple

2022 , Alejo-Reyes, Avelina , Rodríguez Vázquez, Alma Nayeli , Rosas-caro, Julio , Mendoza, Abraham

DC–DC power electronics converters are widely used in many applications, such as renewable energy systems. The multistage-stacked boost architecture (MSBA) converter is a large voltage gain converter whose PWM scheme may reduce a percentage of the output voltage ripple, taking advantage of the symmetry of the voltage signals in capacitors (they are triangular waveforms) to have a symmetry cancelation. The switching ripple is unavoidable; the correct selection of components can reduce it, but this may result in a large amount of stored energy (larger size). The selection of capacitors influences the output voltage ripple magnitude. This article proposes a design methodology that combines a recently introduced PWM scheme with a numerical optimization method to choose the capacitors for the MSBA converter. The objective is to minimize the output voltage ripple by choosing two capacitors simultaneously while ensuring the constraint of a certain (maximum) amount of stored energy in capacitors is not overpassed. The internal optimization was performed with the differential evolution algorithm. The results demonstrate that the proposed method that includes numerical optimization allows having a very low output voltage ripple with the same stored energy in capacitors compared to the traditional converter. In a design exercise, up to 60% reduction was observed in the output voltage ripple with the same stored energy in capacitors.

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