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Item type:Publication, Practical Evaluation of an Optimized LES-QB Converter: Implementation and Experimentation(IEEE, 2025-11-12); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Pro-Game: Single-machine sequencing simulatorThis work presents a game-based learning simulator that simulates a single-machine sequencing problem. The simulator provides a dynamic and interactive platform for industrial engineering students to apply disciplinary concepts, such as operations research, production planning, and optimization techniques, in the pursuit of finding optimal sequencing solutions. The implementation of this simulator in an industrial engineering course demonstrated its efficacy as an engaging and relevant pedagogical tool. Feedback collected from students revealed that the activity not only increased their interest and motivation but also significantly deepened their understanding of the complexities involved in sequencing problems. This study concludes that the use of such simulators in the classroom can dramatically enhance the learning experience by making abstract concepts more tangible and by providing students with a hands-on approach to mastering complex topics. The findings suggest that incorporating simulation-based activities into the curriculum is a valuable strategy for enhancing student outcomes in industrial engineering education. ©The authors ©IEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Investment Portfolio Optimization Using Technical Indicators and White-Box ModelsQuantitative trading has revolutionized in recent years with the integration of machine learning. However, most proposals are complex models that often need help with model understanding and feature importance identification. This study presents a methodology for optimizing investment portfolios using the XGBoost algorithm and a comprehensive set of technical indicators. The primary objective is to maximize returns by accurately predicting stock prices and selecting the most profitable stocks. Our proposal is based on decision trees, eliminating the need for recurrent neural networks or time series representations of data and enabling white-box machine learning models that are easier to interpret. We tried our proposal with real data corresponding to a collection of stocks of the 500 most influential companies in the United States of America, utilizing historical data such as open prices, highest and lowest prices, and trading volume. Experimental results demonstrated that our approach successfully identified the most profitable stocks, outperforming random portfolios and showing significant profit accumulation over time. This approach recognizes the most feasible indicators and facilitates the automatic design of investment portfolios and the analysis of the importance of technical indicators in complex data. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Numerical Analysis of Machining Part Distortion in Aircraft Aluminum StructuresThe inherent residual stresses in the raw materials of large monolithic structural components whereby machining procedures are needed to produce aircraft components, cause deviations, and distortions that are undesired and rise challenges for engineering design and engineering production teams of the aerospace companies. A numerical approach to address part distortion is proposed in this paper. An algorithm was developed and implemented as a finite element subroutine in the software ANSYS APDL, which uses the raw inherent residual stress parameters of the aluminum alloy and the machining locations of a structural specimen to simulate the machining distortion phenomenon in aircraft aluminum structures. This algorithm uses as inputs the finite element mesh of a component, the coefficients of residual stresses functions, and the machining location parameters from where a part is made of a raw material blank. The numerical results predicted the part distortion phenomenon with an Absolute Error of 2.79% with respect to initial experimental measurements of part distortion. Additionally, the proposed approach was used to develop part distortion curves by considering the machining location of the specimen. From these, numerical optimization techniques led to determine the machining location of the representative specimen that attained lower distortions. Such location corresponded to a vertical value around of 3.15 mm for the two simulated residual stresses conditions in the material. An additional measurement was carried out to validate the optimal numerical results and errors below 3% were obtained. Consequently, the proposed approach can be of use to determine, to reduce and to optimize part distortion without further experimental testing in structural aluminum 7050-T7451 alloy aircraft components.14 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An Alternative Method for the Optimum Dynamic Balancing of the Four-Bar Mechanism(2014); Scopus© Citations 1 12 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Multi-threaded Spotted Hyena Optimizer with thread-crossing techniques(2021); Murillo-Suarez, AlfonsoThis paper presents a Multi-threaded version of the Spotted Hyena Optimizer algorithm with thread-crossing techniques (MT-SHO) to improve the ability of the algorithm to explore the search space. The original algorithm is inspired by the hunting behavior of the spotted hyena. Along the different sections of the work, we explain in detail how the original algorithm simulates the spotted hyena's behavior to optimize highly complex mathematical functions and how we handle the procedures and results of the multi-threaded version, with thread-crossing techniques that improve the ability to explore and exploit the search space by letting threads learn between them. We present the experiments used to determine the best value of the parameters used in the parallel version of the algorithm and to prove that our proposal obtains significantly good results we compare the results obtained by evaluating 24 benchmark functions with the results published for the original algorithm as well as other metaheuristic algorithms. © 2021 Elsevier B.V.. All rights reserved.Scopus© Citations 3 33 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, MTGWA: A Multithreaded Gray Wolf Algorithm with Strategies Based on Simulated Annealing and Genetic Algorithms(2021); Scopus© Citations 1 30 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Review on recent implementations of multiobjective and multilevel optimization in sustainable energy economics(2022)Scopus© Citations 1 18 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A new heuristic algorithm to solve Circle Packing problem inspired by nanoscale electromagnetic fields and gravitational effects(2018); Scopus© Citations 3 11 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Intelligent Control Navigation Emerging on Multiple Mobile Robots Applying Social Wound Treatment(2019); C. Souza, Paulo VitorIn robotics, learning new tasks is a complex solving problem. This learning depends on the environment, the robot configuration, the difficulty of the problem task, even the prior knowledge. Reinforcement learning has been widely employed for learning from scratch and policy search; however, it is very time-consuming. Multi-robots, as collaborative learners, have been proposed to improve the speed of learning in robotics. In this paper, we propose a collaborative intelligent control navigation strategy in robots, including a social wound treatment approach, such that robots can jointly learn how to avoid obstacles and move freely around the environment. This collective learning about social treatment aims to detect unexpected or inefficient behaviors of the robots, allowing them to redirect the right tasks with more agility, as observed in some animals. Experimental results over a multiple homogeneous robot system simulation validated our proposal. © 2019 IEEE.Scopus© Citations 2 11 2