Algoritmo genético especializado aplicado ao planejamento da expansão de sistemas de distribuição de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Programação de horários usando um algoritmo genético especializado

Pós-graduação em Engenharia Elétrica - FEIS

Otimização de problemas multimodais usando meta-heurísticas evolutivas

Pós-graduação em Engenharia Elétrica - FEIS

Otimização dinâmica de rotores com eixos em compósito

Pós-graduação em Engenharia Mecânica - FEG

Software baseado em rede neural artificial desenvolvido por meio de algoritmo genético para a classificação morfológica de blastocistos bovinos

Pós-graduação em Biociências - FCLAS

Desenvolvimento de uma ferramenta de otimização para avaliar a expansão da transmissão de energia

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Uma proposta de resolução para problemas de roteirização de veículos baseada no algoritmo genético

The vehicle routing problem is to nd a better route to meet a set of customers who are geographically dispersed using vehicles that are a central repository to which they return after serving customers. These customers have a demand that must be met. Such problems have a wide practical application among them we can mention: school transport, distribution of newspapers, garbage collection, among others. Because it is a classic problem as NP-hard, these problems have aroused interest in the search for viable methods of resolution. In this paper we use the Genetic Algorithm as a resolution

Modelos matemáticos e computacionais em dengue

This work was developed starting the study of traditionals mathematical models that describe the epidemiology of infectious díseases by direct or indirect transmission. We did the classical approach of equilibrium solutions search, its analysis of stability analytically and by numerical solutions. After, we applied these techniques in a compartimental model of Dengue transmission that consider the mosquito population (susceptible vector Vs and 'infected vector VI), human population (suseeptíble humans S, infected humans I and recovered humans R) and just one sorotype floating in this population. We found the equilibrium solutions and from their analises, it was possible find the reprodution rate of dísease and which define if the disease will be endemic or not in the population.- ext, we used the method described a..~, [1] to study the infíuence of seasonalíty at vírus transmission, when it just acts on one of rates related with the vector. Lastly, we made de modeling considering the periodicity of alI rates, thereby building, a modeI with temporal dependence that permits to study periodicity of transmission through of the approach of parametrical ressonance and genetic algorithm

Novo algoritimo genético para problemas de cobertura de conjuntos

The Set Covering Problem (SCP) plays an important role in Operational Research since it can be found as part of several real-world problems. In this work we report the use of a genetic algorithm to solve SCP. The algorithm starts with a population chosen by a randomized greedy algorithm. A new crossover operator and a new adaptive mutation operator were incorporated into the algorithm to intensify the search. Our algorithm was tested for a class of non-unicost SCP obtained from OR-Library without applying reduction techniques. The algorithms found good solutions in terms of quality and computational time. The results reveal that the proposed algorithm is able to find a high quality solution and is faster than recently published approaches algorithm is able to find a high quality solution and is faster than recently published approaches using the OR-Library.

Optimizing urban traffic flow using genetic algorithm with petri net analysis as fitness function

This paper describes a new methodology adopted for urban traffic stream optimization. By using Petri net analysis as fitness function of a Genetic Algorithm, an entire urban road network is controlled in real time. With the advent of new technologies that have been published, particularly focusing on communications among vehicles and roads infrastructures, we consider that vehicles can provide their positions and their destinations to a central server so that it is able to calculate the best route for one of them. Our tests concentrate on comparisons between the proposed approach and other algorithms that are currently used for the same purpose, being possible to conclude that our algorithm optimizes traffic in a relevant manner.

Algoritmo tabu search especializado para o problema de planejamento da expansao de sistemas de transmissão

Pós-graduação em Engenharia Elétrica - FEIS

Otimização da operação de sistemas de distribuição radiais usando um algoritmo genético especializado

Pós-graduação em Engenharia Elétrica - FEIS

Utilização de metaheurísticas combinada a diferentes métodos de aglutinação para a otimização de um processo de torneamento com múltiplas respostas

Pós-graduação em Engenharia Mecânica - FEG

Identificação de parâmetros em sistemas rotativos utilizando funções de otimização e observadores de estado

Pós-graduação em Engenharia Mecânica - FEIS

Controle de fotoassociação caótica com campos externos

The objective of the present work was to study the control of the dynamics of diatomic heteronuclear molecules interacting with electric fields created by lasers. Specifically in this work, the molecular photoassociation phenomenon will be analyzed. At this phenomenon, the atom's relative movement is described by a particle that moves in a morse potential well under the influence of an external time dependant force related to the external field. Based on the optimum control theory (OCT), it is presented at the present work laser pulses that alternate a given initial molecular state to a desirable end state, wich in this work was represented by the minimization of a cost functional that indicates how close. To do so, a computational sistem know as Genetic Algorithm (GA) was developed that can be characterizes as an extremelly eficient technique capable of scanning the solutions space and find results close to the optimum solutions