Mendoza, Abraham
Main Affiliation
Preferred name
Mendoza, Abraham
Official Name
Mendoza Andrade, Abraham
ORCID
0000-0001-8496-4779
Researcher ID
V-4102-2018
Scopus Author ID
56002690300
32 results
Now showing 1 - 10 of 32
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Item type:Publication, 4 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Multi-period multi-product closed loop supply chain network design: A relaxation approach(2021); Scopus© Citations 20 21 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 34 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Collection of Solid Waste in Municipal Areas: Urban Logistics(2019); Maria del Rosario Alvarado Vazquez<jats:p>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.</jats:p>Scopus© Citations 8 5 6 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An Improved Grey Wolf Optimizer for a Supplier Selection and Order Quantity Allocation Problem(2020); ; <jats:p>Supplier selection and order quantity allocation have a strong influence on a company’s profitability and the total cost of finished products. From an optimization perspective, the processes of selecting the right suppliers and allocating orders are modeled through a cost function that considers different elements, such as the price of raw materials, ordering costs, and holding costs. Obtaining the optimal solution for these models represents a complex problem due to their discontinuity, non-linearity, and high multi-modality. Under such conditions, it is not possible to use classical optimization methods. On the other hand, metaheuristic schemes have been extensively employed as alternative optimization techniques to solve difficult problems. Among the metaheuristic computation algorithms, the Grey Wolf Optimization (GWO) algorithm corresponds to a relatively new technique based on the hunting behavior of wolves. Even though GWO allows obtaining satisfying results, its limited exploration reduces its performance significantly when it faces high multi-modal and discontinuous cost functions. In this paper, a modified version of the GWO scheme is introduced to solve the complex optimization problems of supplier selection and order quantity allocation. The improved GWO method called iGWO includes weighted factors and a displacement vector to promote the exploration of the search strategy, avoiding the use of unfeasible solutions. In order to evaluate its performance, the proposed algorithm has been tested on a number of instances of a difficult problem found in the literature. The results show that the proposed algorithm not only obtains the optimal cost solutions, but also maintains a better search strategy, finding feasible solutions in all instances.</jats:p>Scopus© Citations 9 9 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, CAR: heuristics for the inventory routing problem(2020); Scopus© Citations 2 5 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A multi-product dynamic supply chain inventory model with supplier selection, joint replenishment, and transportation cost(2022); Chenxi LiScopus© Citations 15 11 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Modified Simulated Annealing (MSA) Algorithm to Solve the Supplier Selection and Order Quantity Allocation Problem with Non-Linear Freight Rates(2023)Scopus© Citations 8 48 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Positioning automated guided vehicles in a general guide-path layout(2014)5 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Memetic Algorithm for the Cumulative Capacitated Vehicle Routing Problem Including Priority Indexes(2020); ; <jats:p>This paper studies the Cumulative Capacitated Vehicle Routing Problem, including Priority Indexes, a variant of the classical Capacitated Vehicle Routing Problem, which serves the customers according to a certain level of preference. This problem can be effectively implemented in commercial and public environments where customer service is essential, for instance, in the delivery of humanitarian aid or in waste collection systems. For this problem, we aim to minimize two objectives simultaneously, the total latency and the total tardiness of the system. A Mixed Integer formulation is developed and solved using the AUGMECON2 approach to obtain true efficient Pareto fronts. However, as expected, the use of commercial software was able to solve only small instances, up to 15 customers. Therefore, two versions of a Memetic Algorithm with Random Keys (MA-RK) were developed to solve the problem. The computational results show that both algorithms provided good solutions, although the second version obtained denser and higher quality Pareto fronts. Later, both algorithms were used to solve larger instances (20–100 customers). The results were mixed in terms of quality but, in general, the MA-RK v2 consistently outperforms the first version. The models and algorithms proposed in this research provide useful insights for the decision-making process and can be applied to solve a wide variety of business situations where economic, customer service, environmental, and social concerns are involved.</jats:p>Scopus© Citations 14 11 1