Embedding the DIRECT algorithm in a penalty approach for solving engineering design problems

Publicado em CD-ROMIn this paper we investigate the performance of DIRECT algorithm when solving constrained engineering design problems. For this purpose, the hyperbolic penalty approach is employed and the algorithm is modified in order to preserve feasibility of solutions. The algorithm is illustrated on six well–known engineering problems with promising results. Comparisons with other global optimization solvers are reported and discussed

Estudio de aprovechamiento energético en las viviendas mediante energía solar

Publicado em CD-ROMEn la construcción de nuevos edificios surge la idea de una construcción energéticamente eficiente. El objetivo es optimizar los recursos energéticos en nuestros hogares y para ello planteamos dos instalaciones a realizar: energía solar térmica (para producción de agua caliente sanitaria) y energía solar fotovoltaica (para generación de corriente eléctrica). En este artículo se trata de calcular el dimensionamiento de ambas instalaciones en función de la ubicación y las características de la vivienda. Este estudio plantea los modelos matemáticos de ambas instalaciones y con la ayuda de la optimización matemática resolvemos los algoritmos sujetos a unas restricciones. Como aplicación del problema vamos a analizar el caso de una vivienda unifamiliar en una zona climática definida, para así notar la importancia de los parámetros que intervienen en la caracterización de las instalaciones. El objetivo del estudio es determinar de forma rápida y aproximada la viabilidad técnica de ambas instalaciones conociendo escasos datos de partida

Solución de problemas no lineales con restricciones usando DIRECT y una función Lagrangeana aumentada

Publicado em CD-ROMEn este trabajo se pretende hacer la resolución de problemas no lineales con restricciones a través de la utilización del algoritmo DIRECT y de una función Langrangeana aumentada. DIRECT es un método deterministico de optimización global. Ha sido hecha una extensión de DIRECT para resolver problemas con restricciones de tipo igualdad y desigualdad, a través de la utilización de métodos de penalización basados en la función Langrangeana aumentada, teniendo como base los métodos de los multiplicadores. La idea central es resolver el problema de optimización con restricciones a través de la resolución de una sucesión de sub-problemas más simples, esos problemas apenas con restricciones de límites simples, que serán resueltos por DIRECT. Por último, para evaluar el desempeño del método, fue aplicado el método en un conjunto de problemas bien conocidos de optimización global y comparado con otras estrategias

Analysing students' attitudes towards the learning of specialized software

In this article the situation of teaching in engineering courses using specialized software support is evaluated and analysed.The statistics courses in engineering often come off as element of formal exposure to statistical analysis and research methods. The software support during classes intends to facilitate and reinforce learning with computational resolution of statistical specific problems. We report a research that investigates students' attitudes towards computers and their effect on statistics unit performance. The preliminary results of research using a small sample of 47 students enrolled in the experimental statistics unit of the 1st year of the master's degree in industrial engineering from the University of Minho indicate that software perceived usefulness has a positive effect on student success, although perceived ease of use and perceived self-performance do not influence.Fundação para a Ciência e a Tecnologia (FCT

Feature selection optimization of risk factors for coronary heart disease

Cardiovascular disease is a worldwide problem and is the main cause of mortality when coronary heart disease leads to a heart attack. Hence, it is important to evaluate how to prevent this disease considering the symptoms description and physical examinations.This study points out the application and comparison of different performance measures for the classification of heart disease. Firstly, a feedforward neural network was applied to classify heart disease risk, using the well-known Framingham database. Feature selection optimization was performed to identify the most important variables to take into consideration, minimizing the Type II error and maximizing the accuracy. In addition, a multi-objective optimization algorithm was carried out to simultaneously optimize both performance measures. A set of non-dominated solutions representing the trade-offs between objectives were obtained, and gender, age, systolic blood pressure, and glucose level emerged as the principal factors to take into consideration to predict heart disease. The results obtained are promising and show the importance of considering more than one criterion to identify the most important variables.This work has been supported by FCT -Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.Acknowledgments This work has been supported by FCT (Funda¸c˜ao para a Ciˆencia e Tecnologia, Portugal) in the scope of the project PEst-UID/CEC/00319/2013

Cancro do colo do útero: que rastreio?

O cancro do colo do útero é um dos cancros evitáveis mais frequente nas mulheres, Ferlay (2004) e Parkin(2005). O padrão epidemiológico da doença, caracterizado por um período longo entre a detecção das primeiras lesões e a instalação da doença, favorece a sua inclusão em programas de rastreio organizado, por serem custo-eficientes e terem ganhos de saúde associados, ver Anttila (2004), Castellsague (2006) e Koutsky (1998). O presente estudo teve como objectivo auxiliar os elementos da Comissão de Rastreio do Cancro do Colo do Útero na Região Norte na tomada de decisões relativas aos aspectos mais controversos dos rastreios ao cancro do colo do útero: limite de idade das mulheres rastreadas, intervalo entre exames e método utilizado. Assim, construiu-se um modelo matemático, com o intuito de simular os impactos económicos e de saúde, das combinações das várias alternativas de rastreio. Por fim, foi feita uma análise custo-benefício das soluções encontradas e determinou-se a solução, i.e. a opção de rastreio, mais vantajosa.Cervical cancer is one of the most frequent avoidable cancers in women, Ferlay (2004) and Parkin(2005). The natural history of the disease, characterized for a long period between the detection of the rst injuries and invasive cancer, favours its inclusion in organized screening programs, since they are cost-e ective and have clear advantages for the health of the population, see Anttila (2004), Castellsague (2006) and Koutsky (1998). The aim of this study is to construct a mathematical model that can help the elements of the Commission delegated for planning the screening program, to decide about the most controversial aspects: target population, interval between examinations and method to be used. The mathematical model allows to simulate the economical and health impact of all the possible solutions. Finally, a cost-bene t analysis of the combined screening alternatives was done to determine the solution, i.e, the more advantageous screening program

A prescriptive cost model for demand shaping: an application for target costing

Costing tools and traditional cost models are used primarily to calculate costs. However, these models would be more relevant if used as decision-making support tools. That is, they should allow ex-ante rather than ex-post analyses. Nevertheless, cost models tend to follow a linear logic of resources-activities-products (e.g. as it is the case of Activity Based Costing) when uncertainty, variability and dynamics of the current market demand cost models that help decision makers to define which resources are needed to satisfy market needs (e.g. as it is the case of Target Costing), i.e. in a reverse logic. Such models can be designated prescriptive cost models and require significant computational resources to attend the complexity of the problems for which they can be applied. The prescriptive analysis intends to recommend actions based on specified or desired results and it is the most evolved stage of business analytics, far beyond descriptive and predictive approaches. This paper presents and discusses a prescriptive cost model applied in the context of Target Costing. The relevance and validity of this approach are discussed and several opportunities for further work are presented.info:eu-repo/semantics/publishedVersio

On local convergence of stochastic global optimization algorithms

In engineering optimization with continuous variables, the use of Stochastic Global Optimization (SGO) algorithms is popular due to the easy availability of codes. All algorithms have a global and local search character, where the global behaviour tries to avoid getting trapped in local optima and the local behaviour intends to reach the lowest objective function values. As the algorithm parameter set includes a final convergence criterion, the algorithm might be running for a while around a reached minimum point. Our question deals with the local search behaviour after the algorithm reached the final stage. How fast do practical SGO algorithms actually converge to the minimum point? To investigate this question, we run implementations of well known SGO algorithms in a final local phase stage.- This paper has been supported by The Spanish Ministry (RTI2018-095993-B-I00) in part financed by the European Regional Development Fund (ERDF) and by FCT Fundacao para a Ciencia e Tecnologia within the Project Scope: UIDB/00319/2020

Mathematics achievement in engineering : an exploratory study with MIEGI students

Mathematics is a discipline that appears on the syllabus of many courses, including courses in engineering, where it is an essential discipline to the formation of all future engineers, whatever their field of study and work. Despite that, engineering students tend to reveal difficulties with courses based on mathematics. The factors that influence learning mathematics have been the subject of study for several researchers around the world. Researchers attempt to identify variables that explain mathematics achievement, but fail to address university students. In this paper, we present the results of an exploratory study based on industrial engineering students of University of Minho, concerning their grades in the courses of statistics and numerical methods. The preliminary results show that gender is an unexpected and significant factor.Fundação para a Ciência e a Tecnologia (FCT