24 research outputs found

    On the Construction of Pareto-Compliant Combined Indicators

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    The most relevant property that a quality indicator (QI) is expected to have is Pareto compliance, which means that every time an approximation set strictly dominates another in a Pareto sense, the indicator must reflect this. The hypervolume indicator and its variants are the only unary QIs known to be Pareto-compliant but there are many commonly used weakly Pareto-compliant indicators such as R2, IGD+,andɛ+. Currently, an open research area is related to finding new Pareto-compliant indicators whose preferences are different from those of the hypervolume indicator. In this article, we propose a theoretical basis to combine existing weakly Pareto-compliant indicators with at least one being Pareto-compliant, such that the resulting combined indicator is Pareto-compliant as well. Most importantly, we show that the combination of Paretocompliant QIs with weakly Pareto-compliant indicators leads to indicators that inherit properties of the weakly compliant indicators in terms of optimal point distributions. The consequences of these new combined indicators are threefold: (1) to increase the variety of available Pareto-compliant QIs by correcting weakly Pareto-compliant indicators, (2) to introduce a general framework for the combination of QIs, and (3) to generate new selection mechanisms for multiobjective evolutionary algorithms where it is possible to achieve/adjust desired distributions on the Pareto front

    On the utilization of pair-potential energy functions in multi-objective optimization

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    In evolutionary multi-objective optimization (EMO), the pair-potential energy functions (PPFs) have been used to construct diversity-preserving mechanisms to improve Pareto front approximations. Despite PPFs have shown promising results when dealing with different Pareto front geometries, there are still some open research questions to improve the way we employ them. In this paper, we answer three important questions: (1) what is the effect of a crucial parameter of some PPFs?, (2) how do we set the optimal parameter value?, and (3) what is the best PPF in EMO? To solve these questions, we designed a brand-new fast algorithm to generate an approximate solution to a PPF-based subset selection problem and, then, we conducted a comprehensive parametrical study to predict the optimal parameter values using a deep neural network. To show the effectiveness of the PPF-based diversity-preserving mechanisms, we selected two application cases: the generation of reference point sets of benchmark problems (DTLZ, WFG, IDTLZ, IWFG, IMOP, and Viennet) with different Pareto front shapes, and the definition of a PPF-based archive that can be coupled to any multi-objective evolutionary algorithm to construct well-diversified Pareto front approximations. Using several diversity indicators, it is shown that the utilization of PPF-based mechanisms lead to good Pareto front approximations regardless of the Pareto front shape

    Parallel Multi-Objective Evolutionary Algorithms: A Comprehensive Survey

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    Multi-Objective Evolutionary Algorithms (MOEAs) are powerful search techniques that have been extensively used to solve difficult problems in a wide variety of disciplines. However, they can be very demanding in terms of computational resources. Parallel implementations of MOEAs (pMOEAs) provide considerable gains regarding performance and scalability and, therefore, their relevance in tackling computationally expensive applications. This paper presents a survey of pMOEAs, describing a refined taxonomy, an up-to-date review of methods and the key contributions to the field. Furthermore, some of the open questions that require further research are also briefly discussed

    La COVID-19 y su impacto en la salud del adulto mayor

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    Introducción: Ante la pandemia de la COVID-19 los adultos mayores han sido centro de atención por ser el grupo poblacional con mayor impacto en términos de morbilidad y mortalidad ante la enfermedad. Objetivo: Describir el impacto que sobre la salud de los adultos mayores provoca la pandemia por la COVID-19. Envejecimiento poblacional: El envejecimiento poblacional es en la actualidad uno de los fenómenos demográficos de mayor trascendencia mundial.Existen diversas teorías que explican que el envejecimiento conlleva cambios normales; estos cambios biológicos, psicológicos y sociales no necesariamente se relacionan con estados patológicos, pero sí suponen un riesgo mayor de caer en lo que se conoce como síndrome de fragilidad y por ende, en un mayor riesgo de enfermar. Factores de riesgo: Entre los principales factores de riesgo presentes en la población adulta mayor que los hace potencialmente frágiles ante la COVID-19 destacan: La edad, las comorbilidades, enfermedades respiratorias crónicas, disregulación del sistema inmunológico y la residencia en centros sociosanitarios. Manifestaciones clínicas: Inicialmente puede presentarse sin fiebre y estar asociada a decaimiento, desorientación, agitación, adinamia e inapetencia y a la tos. La infección también puede dar lugar a un síndrome respiratorio agudo grave que se asocia a una elevada mortalidad. Conclusiones:La pandemia por la COVID-19 impacta de manera dramática sobre la salud de los adultos mayores, que los convierte especialmente susceptibles de contraer la enfermedad y presentar síntomas graves, por sus comorbilidades, los síndromes geriátricos y la fragilidad asociada al envejecimiento

    An ensemble indicator-based density estimator for evolutionary multi-objective optimization

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    International audienceEnsemble learning is one of the most employed methods in machine learning. Its main ground is the construction of stronger mechanisms based on the combination of elementary ones. In this paper, we employ AdaBoost, which is one of the most well-known ensemble methods, to generate an ensemble indicator-based density estimator for multi-objective optimization. It combines the search properties of five density estimators, based on the hypervolume, R2, IGD+, ε+, and ∆p quality indicators. Through the multi-objective evolutionary search process, the proposed ensemble mechanism adapts itself using a learning process that takes the preferences of the underlying quality indicators into account. The proposed method gives rise to the ensemble indicator-based multi-objective evolutionary algorithm (EIB-MOEA) that shows a robust performance on different multi-objective optimization problems when compared with respect to several existing indicator-based multi-objective evolutionary algorithms

    Bio-inspired computation: where we stand and what's next

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    In recent years, the research community has witnessed an explosion of literature dealing with the adaptation of behavioral patterns and social phenomena observed in nature towards efficiently solving complex computational tasks. This trend has been especially dramatic in what relates to optimization problems, mainly due to the unprecedented complexity of problem instances, arising from a diverse spectrum of domains such as transportation, logistics, energy, climate, social networks, health and industry 4.0, among many others. Notwithstanding this upsurge of activity, research in this vibrant topic should be steered towards certain areas that, despite their eventual value and impact on the field of bio-inspired computation, still remain insufficiently explored to date. The main purpose of this paper is to outline the state of the art and to identify open challenges concerning the most relevant areas within bio-inspired optimization. An analysis and discussion are also carried out over the general trajectory followed in recent years by the community working in this field, thereby highlighting the need for reaching a consensus and joining forces towards achieving valuable insights into the understanding of this family of optimization techniques

    Ecos de la academia: Revista de la Facultad de Educación, Ciencia y Tecnología - FECYT Nro 4

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    Ecos de la academia, Revista de la Facultad de Educación Ciencia y Tecnología es una publicación científica de la Universidad Técnica del Norte, con revisión por pares a doble ciego que publica artículos en idioma español, quichua, portugués e inglés. Se edita con una frecuencia semestral con dos números por año.En ella se divulgan trabajos originales e inéditos generados por los investigadores, docentes y estudiantes de la FECYT, y contribuciones de profesionales de instituciones docentes e investigativas dentro y fuera del país, con calidad, originalidad y relevancia en las áreas de ciencias sociales y tecnología aplicada.Los orígenes de la fotografía en la segunda ciudad de Cataluña: Reus, 1839-1903. Hábitos de consumo y uso de medios digitales en los estudiantes de la Universidad Técnica del Norte. Gastronomía, historia y cultura afrodescendiente de las comunidades Chota y Salinas en Imbabura, Ecuador. Los organizadores gráficos: elementos y procedimientos básicos para su diseño. Análisis del desempeño profesional del graduado de la carrera de Licenciatura en Inglés de la Universidad Técnica del Norte. Uso del software Aleks como complemento en la asignatura de Fundamentos de Matemáticas del curso de nivelación EPN-SENECYT. La educación de postgrado y la enseñanza de Redes Neuronales Artificiales como herramienta versátil para egresados. Home is an uneasty place: Afroperipheralism anda diasporic sensibilities in Wayde Compton’s “The Instrumental”. Respuesta de la carrera de Educación Básica a las necesidades sociales en la Zona 1 del Ecuador. Programa SaludArte: Salud, Alimentación y Movimiento entran a las escuelas para mejorar la calidad educativa. Tendencias de consumo turístico de los Millennials en la ciudad de Ibarra. Los Grupos de Investigación como estrategias para desarrollo de la investigación científica en las instituciones de educación superior ecuatorianas. Paradigmas y modelos pedagógicos de los postulados científicos en el espacio de aula en la Universidad Técnica de Ambato. Predicting academic performance in traditional environments at higher-education institutions using data mining: A review. El Proyecto de Investigación “Muros que hablan. Un recorrido por los graffitis de Imbabura”. Construcción de la marca ciudad. Normas de presentación de artículos científicos en la revista Ecos de la Academia
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