Genetic Algorithms Multi Objective
Mostrando 1-12 de 18 artigos, teses e dissertações.
-
1. Multi-objective optimization of a parallel manipulator for the design of a prosthetic arm using genetic algorithms
Abstract This paper presents a synthesis of a spherical parallel manipulator for a shoulder of a seven-degrees-of-freedom prosthetic human arm using a multi-objective optimization. Three design objectives are considered, namely the workspace, the dexterity, and the actuators torques. The parallel manipulator is modelled considering 13 design parameters in a
Lat. Am. j. solids struct.. Publicado em: 14/05/2018
-
2. Developing and Multi-Objective Optimization of a Combined Energy Absorber Structure Using Polynomial Neural Networks and Evolutionary Algorithms
Abstract In this study a newly developed thin-walled structure with the combination of circular and square sections is investigated in term of crashworthiness. The results of the experimental tests are utilized to validate the Abaqus/ExplicitTM finite element simulations and analysis of the crush phenomenon. Three polynomial meta-models based on the evolved
Lat. Am. j. solids struct.. Publicado em: 2016
-
3. DEVELOPMENT OF A HYBRID FUZZY GENETIC ALGORITHM MODEL FOR SOLVING TRANSPORTATION SCHEDULING PROBLEM
ABSTRACT There has been an increasing public demand for passenger rail service in the recent times leading to a strong focus on the need for effective and efficient use of resources and managing the increasing passenger requirements, service reliability and variability by the railway management. Whilst shortening the passengers’ waiting and travelling time
JISTEM J.Inf.Syst. Technol. Manag.. Publicado em: 2015-12
-
4. Seleção de componentes em ensembles de clasificadores multirrótulo / Component Selection in Ensembles of Multi-label Classifiers
The selection of components in ensembles of classifiers is a very common activity in the field of Machine Learning with several studies showing its effectiveness in obtaining significant gains in accuracy. However, the most studied classification task involves mutually exclusive labels (classes). The objective of this work is to present a study on the select
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 27/07/2012
-
5. Algoritmos evolucionÃrios multipopulaÃÃo na otimizaÃÃo multiobjetiva da remediaÃÃo de Ãguas subterrÃneas / Multi-population Evolutionary Algorithm Multi-Objective Optimization of Groundwater Remediation
Through the last three decades the evolutionary algorithms have been successful on application to many areas. Easily applied, efficiency and confidence are the main advantages of the evolutionary algorithms. In the groundwater remediation, generally, the objectives are the cost minimization, minimization of contaminant presence, maximization of pumping effic
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 24/07/2009
-
6. Algoritmos genéticos multiobjetivos aplicados ao roteamento multicast com qualidade de serviço
Multicast Routing is an effective way to communicate between multiple routers into computer networks. In general, the quality of service (QoS) is required in most of multicast applications. Several researchers have investigated the application of genetic algorithms in multicast Routing with QoS restrictions. The evolutionary environments proposed in this dis
Publicado em: 2009
-
7. Optimization study of airfoil performance using genetic algorithms / Otimização de desempenho de aerofólios supercríticos: uma abordagem baseada em algoritmos genéticos
The objective of present study is analyze the multi-objective optimization applied to transonic airfoils project comparing different ways to define the objective functions. The optimization is evaluated by the genetic algorithm NSGA-II. The results is analyzed using metrics of diversity and optimality for multi-objective problems, which two are proposed. The
Publicado em: 2009
-
8. Extensões da estatística scan espacial utilizando técnicas de otimização multi-objetivo
This work presents three new extensions of Kulldorffs Spatial Scan Statistic for the detection and inference of spatial clusters. Consider a map divided into m regions with known populations at risk and number of cases of some disease. We would like to know if the cases are randomly distributed over the m regions or not; if the cases are not randomly distrib
Publicado em: 2009
-
9. Dilema da diversidade-acurácia: um estudo empírico no contexto de multiclassificadores
Multi-classifier systems, also known as ensembles, have been widely used to solve several problems, because they, often, present better performance than the individual classifiers that form these systems. But, in order to do so, its necessary that the base classifiers to be as accurate as diverse among themselves this is also known as diversity/accuracy dile
Publicado em: 2008
-
10. Contribuição ao estudo dos absorvedores dinâmicos de vibrações não-lineares / A contribution to the study of Nonlinear Vibration Absorbers
In their simplest form, dynamic vibration absorbers (DVAs) are essentially devices of lumped parameters of mass-stiffness-damping that once connected in a given primary structure are capable of absorbing the vibratory energy at the connecting point, providing a reduction of the vibration level. These devices can be used in various configurations and find a n
Publicado em: 2008
-
11. Optimization in design parameters of mechanical systems using multi-objective genetic algorithm / Otimização de parametros de projeto de sistemas mecanicos atraves de algoritmo genetico multi-objetivos
The mechanical systems are designed to be applied to any specific situations, and in this waytheir features should be measured to guarantee confidence to the systems. Their development and analysis expose the designer to a series of unknown parameters from several sources such as material properties, environmental and operational conditions. In terms of math
Publicado em: 2007
-
12. Otimização de carteiras com lotes de compra e custos de transação, uma abordagem por algoritmos genéticos / Portfolio optimization with round lots and transaction costs, an approach with genetic algorithms
Um dos problemas fundamentais em finanças é a escolha de ativos para investimento. O primeiro método para solucionar este problema foi desenvolvido por Markowitz em 1952 com a análise de como a variância dos retornos de um ativo impacta no risco do portifólio no qual o mesmo está inserido. Apesar da importância de sua contribuição, o método desenv
Publicado em: 2007