This paper presents an exhaustive study of the Simple Genetic Algorithm (SGA), Steady State (SSGA) and Replacement (RGA). The performance each method is analyzed in relation to several operators types crossover, selection mutation, as well probabilities crossover mutation with without dynamic change its values during optimization process. In addition, space reduction design variables global elitism are analyzed. All GAs effective when used best operations parameters. For GA, both sets...

In this paper, we discuss multiobjective optimization problems solved by evolutionary algorithms. We present the nondominated sorting genetic algorithm (NSGA) to solve class of and its performance is analyzed comparing results with those obtained four other Finally, NSGA applied TEAM benchmark problem 22 without considering quench physical condition map Pareto-optimum front. The in both analytical electromagnetic show effectiveness.

In this paper, the constraints, in multiobjective optimization problems, are treated as objectives. The constraints transformed two new objectives: one is based on a penalty function and other made equal to number of violated constraints. To ensure convergence feasible Pareto optimal front, constrained individuals eliminated during elitist process. treatment infeasible required some relevant modifications standard Parks Miller technique. Analytical electromagnetic problems presented results...

Foram avaliados 27.523 e 21.746 registros das características conformação, precocidade musculatura à desmana ao sobreano, respectivamente, para estimar os componentes de covariância entre estas pesos corporais medidos nas mesmas idades. Para as análises dos dados, foram empregados modelos animais com efeitos genéticos direto materno efeito ambiente permanente materno. Máxima verossimilhança restrita foi empregada parâmetros genéticos. As estimativas herdabilidade escores desmama 0,13; 0,25...

The distribution network reconfiguration problem (DNRP) refers to the challenge of searching for a given power configuration with better operating conditions, such as minimized energy losses and improved voltage levels. To accomplish that, this paper revisits branch exchange heuristics presents method in which it is coupled other techniques evolutionary metaheuristics cluster analysis. methodology applied four benchmark networks, 33-, 70-, 84-, 136-bus results are compared those available...

This paper is concerned with the problem of evaluating genetic algorithm (GA) operator combinations. Each GA operator, like crossover or mutation, can be implemented according to several different formulations. shows that: 1) performances operators are not independent and 2) merit figures for measuring a performance conflicting. In order account this structure, multiobjective analysis methodology proposed. employed evaluation new (real-biased crossover) that shown bring enhancement. A was...

Objetivou-se, com este trabalho, estimar a herdabilidade (h²) para prenhez de novilhas e sua correlação genética (rg) idade ao primeiro parto (IPP), em animais da raça Nelore. A foi definida três formas: aos 16 meses (Pr16) - as que pariram menos 31 meses, atribuiu-se 1 (sucesso) e, aquelas após 30,99 ou não pariram, 0 (fracasso); 24 (Pr24) até 46 (incluindo Pr16), atribuído 0; novilha (PrN) classificação 2 entre pariram. Os arquivos, analisados pelo Método R Inferência Bayesiana, continham...

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper describes a robust version to the TEAM 22 benchmark optimization problem and presents methodology WCSA (worst case scenario approximation) solve this other similar cases. The multi-objective model was built from its classical configuration by assuming imprecisions in design space. General specific formulas were developed elaborate approach. adds an uncertainty parameter objective...

The purpose of this paper is to introduce a modified approach for the electric field computation at surface overhead transmission line (TL) conductors through finite-element method (FEM). proposed strategy based on spatial transformation, well-known as Kelvin resulting in special way treat unbounded domain. Unlike other applications FEM TLs, suggested procedure aims reduce computational domain and solution time, allowing an efficient numerical evaluation potential gradients, without need...

The result of a multiobjective evolutionary optimization is an efficient solution set surrounded by other candidate points. To choose final solution, we can perform sensitivity study. Applying this methodology, disturbances that occur in real-world design problems are not neglected. This paper presents easy way to the analysis directly from data generated stochastic process. No additional function evaluation required. As example, have solved some concerning electromagnetic devices

In this paper, a hybrid technique for global optimization based on the genetic algorithm and deterministic method is presented. A potential advantage of compared to that can be performed more efficiently. An intrinsic problem techniques related moment stopping stochastic routine launch one. This investigated using some natural criteria commutation between two methods. The results show it possible gain in efficiency accuracy but criterion usually dependent. Finally, solution real problem,...

This paper presents the application of genetic algorithms in optimization an offset reflector antenna. The antenna shape is designed order to obtain a uniform radiation pattern on Brazilian territory. Modified operators are proposed with aim increase efficiency real coded used here.

This paper presents a novel approach for dealing with the structural risk minimization (SRM) applied to general setting of machine learning problem. The formulation is based on fundamental concept that supervised bi-objective optimization problem in which two conflicting objectives should be minimized. are related empirical training error and complexity. In this paper, one Q-norm method compute complexity presented, and, as particular practical case, minimum gradient (MGM) derived relying...

In this paper, three decision making methods-Smarts, Promethee, and a fuzzy algorithm-were utilized to choose the final optimal solution of multiobjective problems. An inverse electromagnetic scattering problem, as well some analytical problems, was considered in study. The posteriori performed by applying each method nondominated front previously met an evolutionary algorithm. results confirm their usage when considering convex but also show that both Smarts Promethee can not always be...

This paper presents a new methodology to analyze the conducted interferences of power converters when its parameters are described by probability density functions rather than numerical values. The is based on determining set surrogate models per frequency converter, which has less input and output variables, shorter simulation time but similar precision for evaluation emissions. approach several advantages compared classical ones, such as Monte Carlo simulations collocation methods. results...

Registros de 24.703 animais da raça Nelore, provenientes seis fazendas, foram utilizados para estimar os coeficientes herdabilidade e a correlação genética relativos às características probabilidade prenhez aos 14 meses (PP14) altura na garupa 450 dias idade (AG450). O modelo matemático incluiu efeitos fixos grupo contemporâneo (181 grupos) classe mãe ao parto (7 classes) PP14 o efeito fixo (584 AG450. Os aleatórios incluídos em ambos modelos genético aditivo do touro residual. componentes...

This paper investigates the use of interval analysis to solve problem maneuvering target tracking, using range-only measures collected by a multistatic radar. The consists in one transmitter, and some receivers working together as radar process is plagued several uncertainty sources that affect directly receivers' measures. As result, tracking can be both imprecise unreliable. study presents an interval-based approach computes set all feasible configurations for which are consistent with...

Uncertainties are commonly present in optimization systems, and when they considered the design stage, problem usually is called a robust problem. Robust problems can be treated as noisy problems, worst case minimization or by considering mean standard deviation values of objective constraint functions. The scenario preferred effects uncertainties on nominal solution critical to application under consideration. Based this scenario, we developed [I]RMOEA (Interval Multi-Objective Evolutionary...