Papers by Marco César Goldbarg
Pesquisa Operacional, 2002
O presente trabalho apresenta uma nova abordagem, denominada Transgenética Computacional. A metáf... more O presente trabalho apresenta uma nova abordagem, denominada Transgenética Computacional. A metáfora baseia-se na utilização de informações meméticas e no emprego dos fluxos extra e intracelulares para planejar e executar manipulações genéticas no contexto dos algoritmos evolucionários. A pesquisa desenvolve duas linhas de algoritmos: a primeira utilizando-se de ambos os fluxos para informar o processo de busca evolucionária; a segunda utiliza-se exclusivamente da manipulação intracelular. São apresentados os agentes da Transgenética Computacional. São examinadas propriedades resultantes da interação cromossomo × agente de manipulação que se mostram semelhantes às do processo imunológico natural. Ao final são relatados resultados computacionais para o Problema Quadrático de Alocação.
International Journal of Innovative Computing and Applications
Brazilian Journal of Development
Brazilian Journal of Development
Este artigo tem como objetivo apresentar um novo problema no contexto do transporte colaborativo ... more Este artigo tem como objetivo apresentar um novo problema no contexto do transporte colaborativo denominado Problema do Passeio Lucrativo com Passageiros e Restrições de Tempo e Custo. O problema consiste em determinar a melhor rota de um courier que precisa realizar serviços em diversos locais. O courier realiza seu percurso em um veículo. Para reduzir custos, o courier pode levar passageiros que compartilham com ele os custos de viagem. Um modelo matemático é proposto o qual é implementado em um solver e aplicado a instâncias do problema. São apresentados algoritmos heurísticos segundo as meta-heurísticas Variable Neighborhood Search e Greedy Randomized Adaptive Search Procedure. São relatados resultados de um experimento computacional com 36 instâncias com até 150 vértices.
Electronic Notes in Theoretical Computer Science
Proceedings of the Genetic and Evolutionary Computation Conference, 2002
This work presents a version of the Piston Pump Unity Tour Problem. The problem is solved by thre... more This work presents a version of the Piston Pump Unity Tour Problem. The problem is solved by three evolutionary algorithms designed according to genetic and transgenetic approaches.
Ieee Congress on Evolutionary Computation, 2010
ABSTRACT This paper presents an experimental analysis of three algorithms for the Oil Derivatives... more ABSTRACT This paper presents an experimental analysis of three algorithms for the Oil Derivatives Distribution Problem with two objectives. The problem consists in scheduling the transmission of oil products from source nodes to terminals in due times. The minimization of two objectives is considered: delivery time and fragmentation, that is, the consecutive transmission of distinct products in the same polyduct. The performance of a Particle Swarm Optimization algorithm is compared to the performance of two versions of the NSGA II algorithm in a set of 15 instances. The results show that the Particle Swarm algorithm outperforms the NSGA II.
2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009
The distribution of petroleum products through pipeline networks is an important problem that ari... more The distribution of petroleum products through pipeline networks is an important problem that arises in production planning of refineries. It consists in determining what will be done in each production stage given a time horizon, concerning the distribution of products from source nodes to demand nodes, passing through intermediate nodes. Constraints concerning storage limits, delivering time, sources availability, among others, have to be satisfied. This problem can be viewed as a bi-objective problem that aims at minimizing time and the successive transmission of different products in the same pipe. In this paper, a discrete particle swarm optimization algorithm is applied to this problem. The results obtained with the proposed approach are compared with the results obtained by two genetic algorithms proposed previously for the problem.
Lecture Notes in Computer Science, 2006
Combinatorial optimization problems with multiple objectives are, in general, more realistic repr... more Combinatorial optimization problems with multiple objectives are, in general, more realistic representations of practical situations than their counterparts with a single-objective. The bi-objective minimum spanning tree problem is a NP-hard problem with applications in ...
Proceedings of the 2008 Acm Symposium on Applied Computing, 2008
Page 1. Selecting Beam Directions in Radiotherapy with an Evolutionary Algorithm Marco C.Goldbarg... more Page 1. Selecting Beam Directions in Radiotherapy with an Evolutionary Algorithm Marco C.Goldbarg UFRN Campus Universitário, Lagoa Nova Natal, Brazil [email protected] Elizabeth FG Goldbarg UFRN Campus Universitário, Lagoa Nova Natal, Brazil [email protected] ...
Page 1. MIC'2001 - 4th Metaheuristics International Conference 321 Extra-Intracellular Trans... more Page 1. MIC'2001 - 4th Metaheuristics International Conference 321 Extra-Intracellular Transgenetic Algorithm applied to the Graph Coloring Problem Marco César Goldbarg ∗ Elizabeth Gouvêa ∗ Lívia MM Silva ∗ * Umiversidade ...
Proceedings of the 6th European Conference on Evolutionary Computation in Combinatorial Optimization, 2006
Preface Metaheuristics have often been shown to be effective for difficult combinatorial optimiza... more Preface Metaheuristics have often been shown to be effective for difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms, and ant colony optimization. Successfully solved problems include scheduling, timetabling, network design, transportation and distribution problems, vehicle routing, the traveling salesperson problem, satisfiability, packing and cutting problems, planning problems, and general mixed integer programming. The EvoCOP event series started in 2001 and has been held annually since then. It was the first specifically dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems. Evolutionary computation involves the study of problem-solving and optimization techniques inspired by principles of natural evolution and genetics. Following the general trend of hybrid metaheuristics and diminishing boundaries between the different classes of metaheuristics, EvoCOP has broadened its scope over the last years and invited submissions on any kind of metaheuristic for combinatorial optimization problems. This volume contains the
Wseas Transactions on Systems, 2004
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Papers by Marco César Goldbarg