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

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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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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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Finding optimal dwell points for automated guided vehicles in general guide-path layouts

2015 , José A. Ventura , Subramanian Pazhani , Mendoza, Abraham

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EVALUATING THE IMPACT OF ORDER PICKING STRATEGIES ON THE ORDER FULFILMENT TIME: A SIMULATION STUDY

2019 , Urzúa, Mercedes , Mendoza, Abraham , Akbal González

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CARE: Heuristics for two-stage multi-product inventory routing problems with replenishments

2016 , Ramkumar Nambirajan , Mendoza, Abraham , Subramanian Pazhani , T.T. Narendran , K. Ganesh

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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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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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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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A methodology for increasing revenue in fashion retail industry

2018 , Nucamendi-Guillén, Samuel , Moreno, Miguel A. , Mendoza, Abraham

Purpose Fashion retail companies typically exhibit short life-cycles, high volatility and low predictability. Therefore, their success is largely determined by the organisation’s flexibility and responsiveness. The purpose of this paper is to present a methodology to facilitate inventory control to minimise both shortages and excess inventory for a multi-product, multi-period finite time horizon inventory problem by using statistical and stochastic analysis. Design/methodology/approach The proposed methodology operates in two phases: the first phase consists on determining an aggregate plan (AP) that will be used for monitoring the behaviour of the items during the time horizon. This plan is obtained by statistically analysing historical data related to sales and inventory shortages and is used to determine a demand forecast during the time horizon that allows to handle with potential disruptions derived from real demand variations. Finally, supply replenishment policies are defined to facilitate the monitoring process during the second phase. For the second phase, the behaviour of real demand for every item is captured into a database and compared against its projected demand (from the AP). If needed, adjustments are made in the procurement of future deliveries to reduce the probability of having shortages and/or excess inventory. Findings A case study in a Mexican fashion retail company was conducted to assess the performance of the methodology. Results indicate that shortage in early periods can be reduced totally for certain products while, for others, the reduction is about 90.5 per cent. In addition, the incomes of the company were increased over 57 per cent. Research limitations/implications Even when the success of the methodology has been shown, cultural and behavioural factors were not considered. An extensive study is suggested to determine if these factors should be included to enhance the performance of the methodology. Practical implications A case study of a Mexican fashion retail company was conducted to assess the performance of the proposed methodology. The methodology is easy to implement and effectively and quickly responds to disruptions in the demand and it also significantly reduces the level of shortages while increasing sales and revenue for the company. Originality/value This paper proposes a methodology that is able to anticipate product’s behaviour from early weeks. Additionally, replenishment policies allow to quickly adjust future orders to guarantee the availability of items and minimise overstock.

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Production and distribution planning in a supply chain network

2011-01-01 , Mendoza, Abraham , Ventura, José A. , Cho, Seong Rae

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