Papers by Irving Barragan Vite
Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI
El problema de corte abordado en este documento consiste en minimizar el desperdicio total produc... more El problema de corte abordado en este documento consiste en minimizar el desperdicio total producido al cortar un conjunto de piezas pequeñas en una secuencia determinada a partir de piezas de material más grandes. El algoritmo del búfalo Africano ha sido empleado exitosamente para resolver problemas de tipo combinatorio. Una de las dificultades de este algoritmo es generar soluciones discretas para esta clase de problemas discretos. En este trabajo se emplea una variante discreta del algoritmo del búfalo Africano en la que se compara una técnica de cruza así como la técnica del valor del orden clasificado para obtener soluciones discretas. Se usa un conjunto de diez instancias de diferente complejidad para realizar la comparación de estas técnicas. Los resultados muestran que la técnica de cruza supera a las otras en cuanto a la calidad de las soluciones. Luego estos resultados se comparan contra otros algoritmos para evaluar su desempeño.
IEEE Access
An electrocardiogram (ECG) is a non-invasive study used for the diagnosis of cardiac arrhythmias ... more An electrocardiogram (ECG) is a non-invasive study used for the diagnosis of cardiac arrhythmias (CAs). The identification of a cardiac arrhythmia depends on its classification. This classification has been approached through different strategies, both mathematical and computational. In this work, a new computational model based on the particle swarm optimization (PSO) algorithm and convolutional neural network (CNN) is proposed for the classification of five classes of CAs obtained from the MIT-BIH Arrhythmia Dataset (MITDB). The goal of the PSO is to optimize the hyperparameters that define the layered architecture of a CNN, to increase the accuracy and decrease the categorical crossentropy error (CE). The proposed model found a satisfactory layered architecture in 17.68 hours, obtaining an accuracy of 98% and 97%, a CE of 0.044968 and 0.084768, in training and testing, respectively. These results demonstrate that the proposed model is reliable and represents an innovative approach because it allows dispensing with the manual selection of the hyperparameters of the layered architecture of a CNN.
IEEE Access, 2023
An electrocardiogram (ECG) is a non-invasive study used for the diagnosis of cardiac arrhythmias ... more An electrocardiogram (ECG) is a non-invasive study used for the diagnosis of cardiac arrhythmias (CAs). The identification of a cardiac arrhythmia depends on its classification. This classification has been approached through different strategies, both mathematical and computational. In this work, a new computational model based on the particle swarm optimization (PSO) algorithm and convolutional neural network (CNN) is proposed for the classification of five classes of CAs obtained from the MIT-BIH Arrhythmia Dataset (MITDB). The goal of the PSO is to optimize the hyperparameters that define the layered architecture of a CNN, to increase the accuracy and decrease the categorical crossentropy error (CE). The proposed model found a satisfactory layered architecture in 17.68 hours, obtaining an accuracy of 98% and 97%, a CE of 0.044968 and 0.084768, in training and testing, respectively. These results demonstrate that the proposed model is reliable and represents an innovative approach because it allows dispensing with the manual selection of the hyperparameters of the layered architecture of a CNN.
Mathematics
The Flexible Job Shop Scheduling Problem (FJSSP) continues to be studied extensively to test new ... more The Flexible Job Shop Scheduling Problem (FJSSP) continues to be studied extensively to test new metaheuristics and because of its closeness to current production systems. A variant of the FJSSP uses fuzzy processing times instead of fixed times. This paper proposes a new algorithm for FJSSP with fuzzy processing times called the global neighborhood with hill-climbing algorithm (GN-HC). This algorithm performs solution exploration using simple operators concurrently for global search neighborhood handling. For local search, random restart hill-climbing is applied at each solution to find the best machine for each operation. For the selection of operations in hill climbing, a record of the operations defining the fuzzy makespan is employed to use them as a critical path. Finally, an estimation of the crisp makespan with the longest processing times in hill climbing is made to improve the speed of the GN-HC. The GN-HC is compared with other recently proposed methods recognized for the...
ArXiv, 2020
Complexity has been a recurrent research topic in cellular automata because they represent system... more Complexity has been a recurrent research topic in cellular automata because they represent systems where complex behaviors emerge from simple local interactions. A significant amount of previous research has been conducted proposing instances of complex cellular automata; however, most of the proposed methods are based on a careful search or a meticulous construction of evolution rules. This paper presents the emergence of complex behaviors based on reversible cellular automata. In particular, this paper shows that reversible cellular automata represent an adequate framework to obtain complex behaviors adding only new random states. Experimental results show that complexity can be obtained from reversible cellular automata appending a proportion of about two times more states at random than the original number of states in the reversible automaton. Thus, it is possible to obtain complex cellular automata with dozens of states. Complexity appears to be commonly obtained from reversib...
Applied Sciences
This work presents a novel hybrid algorithm called GA-RRHC based on genetic algorithms (GAs) and ... more This work presents a novel hybrid algorithm called GA-RRHC based on genetic algorithms (GAs) and a random-restart hill-climbing (RRHC) algorithm for the optimization of the flexible job shop scheduling problem (FJSSP) with high flexibility (where every operation can be completed by a high number of machines). In particular, different GA crossover and simple mutation operators are used with a cellular automata (CA)-inspired neighborhood to perform global search. This method is refined with a local search based on RRHC, making computational implementation easy. The novel point is obtained by applying the CA-type neighborhood and hybridizing the aforementioned two techniques in the GA-RRHC, which is simple to understand and implement. The GA-RRHC is tested by taking four banks of experiments widely used in the literature and comparing their results with six recent algorithms using relative percentage deviation (RPD) and Friedman tests. The experiments demonstrate that the GA-RRHC is a ...
Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI
Técnicas basadas en población inspiradas en la naturaleza, han demostrado ser efectivas para reso... more Técnicas basadas en población inspiradas en la naturaleza, han demostrado ser efectivas para resolver problemas complejos de optimización. Estos métodos son capaces de encontrar los parámetros óptimos de controladores. En este trabajo se diseña un controlador Proporcional Derivativo (PD) compensado, el cual permite a un UAV (unmanned aerial vehicle) seguir una trayectoria predeterminada. Los parámetros óptimos del controlador son determinados mediante la minimización de la función costo, calculada como el error entre las trayectorias deseadas y las reales en el espacio tridimensional. Además, se comparan seis diferentes algoritmos meta-heurísticos para su sintonización: Optimización por Nube de Partículas (PSO), la variante del Algoritmo de Evolución Diferencial (L-SHADE), Algoritmo de Optimización de Lobos (GWO), Optimización por Pastoreo de Elefantes (EHO), Algoritmo de Optimización de Ballenas (WOA) y el Algoritmo de Autómata Celular de Estado Continuo (CCAA). Los resultados de l...
Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI
Una arritmia cardíaca es un latido irregular del corazón que se traduce en un impulso eléctrico a... more Una arritmia cardíaca es un latido irregular del corazón que se traduce en un impulso eléctrico anormal, y su tipo se define por el ritmo y duración. Su clasificación ha sido abordada en diferentes campos de la ciencia, destacando el uso de algoritmos de aprendizaje profundo. La presente investigación, utilizó un modelo híbrido entre Redes Neuronales Convolucionales y el algoritmo metaheurístico de Optimización por Enjambre de Partículas; para la clasificación de arritmias cardíacas. El metaheurístico se encargó de optimizar la arquitectura de capas de la red neuronal, a través de la minización de la pérdida durante el entrenamiento y prueba. Los datos se obtuvieron del MIT-BIH Arrhythmia dataset, donde se describen cinco categorías de arritmias. Los resultados logrados demostraron que el metaheurístico es un algoritmo confiable en la búsqueda de la mejor arquitectura de capas, logrando obtener una exactitud del 97%, lo que significa que el uso de técnicas metaheurísticas es una opc...
Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI
El problema de corte unidimensional consiste en cortar un objeto o stock, cuya longitud puede ser... more El problema de corte unidimensional consiste en cortar un objeto o stock, cuya longitud puede ser finita o infinita, para producir objetos más pequeños o ítems con longitud finita. Este problema aparece en una gran cantidad de industrias alrededor del mundo. En este trabajo se propone adaptar el algoritmo de optimización del búfalo Africano con el objetivo de reducir los stocks necesarios para satisfacer la demanda de ítems. El algoritmo se probó en un conjunto de instancias que son referencia para este problema. Los resultados indican que el algoritmo consigue soluciones competitivas de acuerdo a la minimización del stock.
Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI
Este artículo aborda la programación de tareas en el Flexible Job Shop Scheduling Problem (FJSSP)... more Este artículo aborda la programación de tareas en el Flexible Job Shop Scheduling Problem (FJSSP). En este sistema de manufactura es necesario incrementar el número de trabajos a procesar debido a las condiciones actuales del sector industrial en donde existe un aumento en la demanda de productos, lo que conlleva a incrementar la producción. Para encontrar una programación de tareas cercana al óptimo. Se propone un método de optimización híbrida utilizando una búsqueda global basada en algoritmos genéticos (AG) que tienen buena diversificación y para la búsqueda local se aplica una escalada de colinas simple con reinicio (ECR) para mejorar cada solución. La combinación de estas metaheurísticas obtiene el equilibrio necesario para encontrar la mejor programación de tareas con el fin de minimizar el makespan como función costo. Se implementó el algoritmo propuesto en Matlab, para comprobar su eficiencia se compararon los resultados con investigaciones recientemente publicadas.
Applied sciences, Mar 26, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
PÄDI Boletín Científico de Ciencias Básicas e Ingenierías del ICBI, 2018
Para problemas multi-objetivo, los métodos de poda actuales son útiles para reducir de forma cons... more Para problemas multi-objetivo, los métodos de poda actuales son útiles para reducir de forma considerable la cantidad de soluciones que son obtenidas en un frente de Pareto, además de satisfacer la mayoría de las características que el decisor requiere para tomar una decisión correcta en la elección de una solución. Sin embargo, estos métodos pueden llegar a ser muy complejos y carecer de algunas propiedades relevantes para calcular la solución óptima. Basándonos en las necesidades que el decisor tiene para seleccionar la mejor solución en un problema de planeación de la producción, este trabajo presenta un nuevo método de poda que obtiene mejores valores en las funciones objetivo, un número no mayor a 10 soluciones para que el decisor sea capaz de hacer una elección rápida y precisa, y está basado en operaciones simples que facilitan su implementación.
Applied Sciences, 2021
The development of quadrotor unmanned aerial vehicles (QUAVs) is a growing field due to their wid... more The development of quadrotor unmanned aerial vehicles (QUAVs) is a growing field due to their wide range of applications. QUAVs are complex nonlinear systems with a chaotic nature that require a controller with extended dynamics. PD and PID controllers can be successfully applied when the parameters are accurate. However, this parameterization process is complicated and time-consuming; most of the time, parameters are chosen by trial and error without guaranteeing good performance. The originality of this work is to present a novel nonlinear mathematical model with aerodynamic moments and forces in the Newton–Euler formulation, and identify metaheuristic algorithms applied to parameter optimization of compensated PD and PID controls for tracking the trajectories of a QUAV. Eight metaheuristic algorithms (PSO, GWO, HGS, LSHADE, LSPACMA, MPA, SMA and WOA) are reported, and RMSE is used to measure each dynamic performance of the simulations. For the PD control, the best performance is ...
DYNA INGENIERIA E INDUSTRIA, 2018
Complexity has been a recurrent research topic in cellular automata because they represent system... more Complexity has been a recurrent research topic in cellular automata because they represent systems where complex behaviors emerge from simple local interactions. A significant amount of previous research has been conducted proposing instances of complex cellular automata; however, most of the proposed methods are based on a careful search or a meticulous construction of evolution rules. This paper presents the emergence of complex behaviors based on reversible cellular automata. In particular, this paper shows that reversible cellular automata represent an adequate framework to obtain complex behaviors adding only new random states. Experimental results show that complexity can be obtained from reversible cellular automata appending a proportion of about two times more states at random than the original number of states in the reversible automaton. Thus, it is possible to obtain complex cellular automata with dozens of states. Complexity appears to be commonly obtained from reversib...
PeerJ Computer Science
The Flexible Job Shop Scheduling Problem (FJSP) is a combinatorial problem that continues to be s... more The Flexible Job Shop Scheduling Problem (FJSP) is a combinatorial problem that continues to be studied extensively due to its practical implications in manufacturing systems and emerging new variants, in order to model and optimize more complex situations that reflect the current needs of the industry better. This work presents a new metaheuristic algorithm called the global-local neighborhood search algorithm (GLNSA), in which the neighborhood concepts of a cellular automaton are used, so that a set of leading solutions called smart-cells generates and shares information that helps to optimize instances of the FJSP. The GLNSA algorithm is accompanied by a tabu search that implements a simplified version of the Nopt1 neighborhood defined in Mastrolilli & Gambardella (2000) to complement the optimization task. The experiments carried out show a satisfactory performance of the proposed algorithm, compared with other results published in recent algorithms, using four benchmark sets an...
Inf. Sci., 2017
Reversible one-dimensional cellular automata are studied from the perspective of Welch Sets. This... more Reversible one-dimensional cellular automata are studied from the perspective of Welch Sets. This paper presents an algorithm to generate random Welch sets that define a reversible cellular automaton. Then, properties of Welch sets are used in order to establish two bipartite graphs describing the evolution rule of reversible cellular automata. The first graph gives an alternative representation for the dynamics of these systems as block mappings and shifts. The second graph offers a compact representation for the evolution rule of reversible cellular automata. Both graphs and their matrix representations are illustrated by the generation of random reversible cellular automata with 6 and 18 states.
2021 3rd International Conference on Advanced Information Science and System (AISS 2021)
Inf. Sci., 2021
The emergence of complex behaviors in cellular automata is an area that has been widely developed... more The emergence of complex behaviors in cellular automata is an area that has been widely developed in recent years with the intention to generate and analyze automata that produce space-moving patterns or gliders that interact in a periodic background. Frequently, this type of automata has been found through either an exhaustive search or a meticulous construction of the evolution rule. In this study, the specification of cellular automata with complex behaviors was obtained by utilizing randomly generated specimens. In particular, it proposed that a cellular automaton of $n$ states should be specified at random and then extended to another automaton with a higher number of states so that the original automaton operates as a periodic background where the additional states serve to define the gliders. Moreover, this study presented an explanation of this method. Furthermore, the random way of defining complex cellular automata was studied by using mean-field approximations for various...
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Papers by Irving Barragan Vite