Uma colônia de formigas para o caminho mais curto multiobjetivo

Multi-objective combinatorial optimization problems have peculiar characteristics that require optimization methods to adapt for this context. Since many of these problems are NP-Hard, the use of metaheuristics has grown over the last years. Particularly, many different approaches using Ant Colony Optimization (ACO) have been proposed. In this work, an ACO is proposed for the Multi-objective Shortest Path Problem, and is compared to two other optimizers found in the literature. A set of 18 instances from two distinct types of graphs are used, as well as a specific multiobjective performance assessment methodology. Initial experiments showed that the proposed algorithm is able to generate better approximation sets than the other optimizers for all instances. In the second part of this work, an experimental analysis is conducted, using several different multiobjective ACO proposals recently published and the same instances used in the first part. Results show each type of instance benefits a particular type of instance benefits a particular algorithmic approach. A new metaphor for the development of multiobjective ACOs is, then, proposed. Usually, ants share the same characteristics and only few works address multi-species approaches. This works proposes an approach where multi-species ants compete for food resources. Each specie has its own search strategy and different species do not access pheromone information of each other. As in nature, the successful ant populations are allowed to grow, whereas unsuccessful ones shrink. The approach introduced here shows to be able to inherit the behavior of strategies that are successful for different types of problems. Results of computational experiments are reported and show that the proposed approach is able to produce significantly better approximation sets than other methods

Modelos matemáticos para o problema integrado de dimensionamento de lotes e corte de estoque undimensional

Pós-graduação em Matemática - IBILCE

Reformulações e relaxação Lagrangiana para o problema de dimensionamento de lotes com várias plantas

Pós-graduação em Matemática - IBILCE

Utilização de um algoritmo de caminho mínimo no processo de recolhimento do palhiço da cana-de-açúcar

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Avaliação de desempenho de algoritmos de alocação de comprimento de onda em redes ópticas WDM

Neste trabalho estudamos alguns algoritmos de alocação de comprimento de onda em redes ópticas WDM (Wavelength Division Multiplexing). O objetivo para estudar os algoritmos de alocação first-fit, least-used e most-used está baseado na estratégia adotada para estudar o Problema RWA. A estratégia toma como base a visão geral do problema que envolve os algoritmos de roteamento e os algoritmos de alocação de comprimento de onda, e tendo como métrica principal para seus resultados a probabilidade de bloqueio. Este trabalho apresenta uma visão diferenciada para o problema e considera-se que a alocação de comprimentos de onda se sobrepõe, em importância, à ação de roteamento em redes ópticas. Essa percepção ocorre quando se analisa o problema RWA a partir do critério clássico usado no estabelecimento de uma rota: a escolha do caminho mais curto entre a origem e o destino. Apesar da identificação de um caminho mais curto, isso não garante, em redes ópticas, que ele será o utilizado, pois é necessário que haja para aquele caminho, um comprimento de onda adequado. Foi utilizada uma ferramenta de simulação para redes WDM denominada OWNS para realizar uma análise do problema RWA. Os resultados obtidos são apresentados graficamente e em uma das simulações observou-se uma forte tendência de queda na probabilidade de bloqueio e uma boa vazão no trafego da rede com isso possibilitando um aumento na capacidade de transmissão da rede. Por fim, este texto apresenta uma discussão sobre os diferenciais e limitações deste trabalho, e apresenta direcionamentos para investigações futuras neste campo de estudo.

Wavelength assignment using a hybrid evolutionary computation to reduce cross-phase modulation

In this paper, we propose a hybrid methodology based on Graph-Coloring and Genetic Algorithm (GA) to solve the Wavelength Assignment (WA) problem in optical networks, impaired by physical layer effects. Our proposal was developed for a static scenario where the physical topology and traffic matrix are known a priori. First, we used fixed shortest-path routing to attend demand requests over the physical topology and the graph-coloring algorithm to minimize the number of necessary wavelengths. Then, we applied the genetic algorithm to solve WA. The GA finds the wavelength activation order on the wavelengths grid with the aim of reducing the Cross-Phase Modulation (XPM) effect; the variance due to the XPM was used as a function of fitness to evaluate the feasibility of the selected WA solution. Its performance is compared with the First-Fit algorithm in two different scenarios, and has shown a reduction in blocking probability up to 37.14% when considered both XPM and residual dispersion effects and up to 71.42% when only considered XPM effect. Moreover, it was possible to reduce by 57.14% the number of wavelengths.

Políticas de alocação de espectro em roteamento baseado em balanceamento de cargas e fragmentação para redes ópticas elásticas

A natureza rígida de redes de multiplexação por divisão de comprimentos de onda (WDM) provoca exploração ineficiente de capacidade espectral. Dessa forma, redes flexíveis são um possível avanço para a tecnologia óptica por viabilizarem melhor aproveitamento dos recursos espectrais disponíveis. Com o intuito de aferir a possível aplicabilidade de redes flexíveis, este trabalho propõe uma estratégia de avaliação de desempenho baseada em simulações e comparações entre resultados obtidos. Para tanto, várias simulações a tempo discreto foram implementadas em dois simuladores desenvolvidos em Matlab a fim de analisar diferentes políticas de alocação de espectro (First-Fit, Smallest-Fit, Exact-Fit e Random-Fit) em três algoritmos de roteamento por caminhos ópticos não híbridos: o roteamento por fragmentação externa (FA), por caminhos mais curtos com máxima eficiência de reuso espectral (SPSR) e por balanceamento de cargas (BLSA). Duas topologias de rede foram utilizadas: um pequeno subconjunto de 6 nós da Cost239 e uma topologia aleatória de 7 nós. Admitindo-se que efeitos de camada física não foram configurados como restrições, foram realizadas comparações entre as diversas técnicas estudadas, objetivando-se apontar, baseado nas especificidades dos cenários propostos, qual o método mais adequado de alocação espectral em termos de frequência de bloqueio entre as quatro políticas de alocação de espectro consideradas.

Formulações fortes para o problema de dimensionamento de lotes com várias plantas

This paper considers the multi-plant lot sizing problem. Each item can be produced in any plant and it is possible to meet the demand of a particular plant with production from one (or several) other plants, in this case, incurs a transfer cost. The objective is todevelop strong formulations for this problem. Reformulations that based on the shortest path problem and facility location problem are investigated. Finally, some computational results are presented comparing all the proposed formulations.

Reformulation and a Lagrangian heuristic for lot sizing problem on parallel machines

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelos Matemáticos e Métodos de Solução para Problemas de Dimensionamento de Lotes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelos matemáticos para o problema integrado de dimensionamento de lotes e corte de estoque unidimensional

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Utilização de um algoritmo de caminho mínimo no processo de recolhimento do palhiço da cana-de-açúcar

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Performance Analysis of Sparse Traffic Grooming in WDM Mesh Networks

Sparse traffic grooming is a practical problem to be addressed in heterogeneous multi-vendor optical WDM networks where only some of the optical cross-connects (OXCs) have grooming capabilities. Such a network is called as a sparse grooming network. The sparse grooming problem under dynamic traffic in optical WDM mesh networks is a relatively unexplored problem. In this work, we propose the maximize-lightpath-sharing multi-hop (MLS-MH) grooming algorithm to support dynamic traffic grooming in sparse grooming networks. We also present an analytical model to evaluate the blocking performance of the MLS-MH algorithm. Simulation results show that MLSMH outperforms an existing grooming algorithm, the shortest path single-hop (SPSH) algorithm. The numerical results from analysis show that it matches closely with the simulation. The effect of the number of grooming nodes in the network on the blocking performance is also analyzed.

Identification of literary movements using complex networks to represent texts

The use of statistical methods to analyze large databases of text has been useful in unveiling patterns of human behavior and establishing historical links between cultures and languages. In this study, we identified literary movements by treating books published from 1590 to 1922 as complex networks, whose metrics were analyzed with multivariate techniques to generate six clusters of books. The latter correspond to time periods coinciding with relevant literary movements over the last five centuries. The most important factor contributing to the distinctions between different literary styles was the average shortest path length, in particular the asymmetry of its distribution. Furthermore, over time there has emerged a trend toward larger average shortest path lengths, which is correlated with increased syntactic complexity, and a more uniform use of the words reflected in a smaller power-law coefficient for the distribution of word frequency. Changes in literary style were also found to be driven by opposition to earlier writing styles, as revealed by the analysis performed with geometrical concepts. The approaches adopted here are generic and may be extended to analyze a number of features of languages and cultures.

The structure and resilience of financial market networks

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience. (C) 2012 American Institute of Physics. [doi:10.1063/1.3683467]