Low levels of realized seed and pollen gene flow and strong spatial genetic structure in a small, isolated and fragmented population of the tropical tree Copaifera langsdorffii Desf

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

O problema do caixeiro viajante alugador : um estudo algorítmico

The Car Rental Salesman Problem (CaRS) is a variant of the classical Traveling Salesman Problem which was not described in the literature where a tour of visits can be decomposed into contiguous paths that may be performed in different rental cars. The aim is to determine the Hamiltonian cycle that results in a final minimum cost, considering the cost of the route added to the cost of an expected penalty paid for each exchange of vehicles on the route. This penalty is due to the return of the car dropped to the base. This paper introduces the general problem and illustrates some examples, also featuring some of its associated variants. An overview of the complexity of this combinatorial problem is also outlined, to justify their classification in the NPhard class. A database of instances for the problem is presented, describing the methodology of its constitution. The presented problem is also the subject of a study based on experimental algorithmic implementation of six metaheuristic solutions, representing adaptations of the best of state-of-the-art heuristic programming. New neighborhoods, construction procedures, search operators, evolutionary agents, cooperation by multi-pheromone are created for this problem. Furtermore, computational experiments and comparative performance tests are conducted on a sample of 60 instances of the created database, aiming to offer a algorithm with an efficient solution for this problem. These results will illustrate the best performance reached by the transgenetic algorithm in all instances of the dataset

Arquitetura multiagente baseada em nuvem de partículas para hibridização de metaheurísticas

This thesis proposes an architecture of a new multiagent system framework for hybridization of metaheuristics inspired on the general Particle Swarm Optimization framework (PSO). The main contribution is to propose an effective approach to solve hard combinatory optimization problems. The choice of PSO as inspiration was given because it is inherently multiagent, allowing explore the features of multiagent systems, such as learning and cooperation techniques. In the proposed architecture, particles are autonomous agents with memory and methods for learning and making decisions, using search strategies to move in the solution space. The concepts of position and velocity originally defined in PSO are redefined for this approach. The proposed architecture was applied to the Traveling Salesman Problem and to the Quadratic Assignment Problem, and computational experiments were performed for testing its effectiveness. The experimental results were promising, with satisfactory performance, whereas the potential of the proposed architecture has not been fully explored. For further researches, the proposed approach will be also applied to multiobjective combinatorial optimization problems, which are closer to real-world problems. In the context of applied research, we intend to work with both students at the undergraduate level and a technical level in the implementation of the proposed architecture in real-world problems

Uma análise experimental de abordagens heurísticas aplicadas ao problema do caixeiro viajante

Due to great difficulty of accurate solution of Combinatorial Optimization Problems, some heuristic methods have been developed and during many years, the analysis of performance of these approaches was not carried through in a systematic way. The proposal of this work is to make a statistical analysis of heuristic approaches to the Traveling Salesman Problem (TSP). The focus of the analysis is to evaluate the performance of each approach in relation to the necessary computational time until the attainment of the optimal solution for one determined instance of the TSP. Survival Analysis, assisted by methods for the hypothesis test of the equality between survival functions was used. The evaluated approaches were divided in three classes: Lin-Kernighan Algorithms, Evolutionary Algorithms and Particle Swarm Optimization. Beyond those approaches, it was enclosed in the analysis, a memetic algorithm (for symmetric and asymmetric TSP instances) that utilizes the Lin-Kernighan heuristics as its local search procedure

Uma abordagem por nuvem de partículas para problemas de otimização combinatória

Combinatorial optimization problems have the goal of maximize or minimize functions defined over a finite domain. Metaheuristics are methods designed to find good solutions in this finite domain, sometimes the optimum solution, using a subordinated heuristic, which is modeled for each particular problem. This work presents algorithms based on particle swarm optimization (metaheuristic) applied to combinatorial optimization problems: the Traveling Salesman Problem and the Multicriteria Degree Constrained Minimum Spanning Tree Problem. The first problem optimizes only one objective, while the other problem deals with many objectives. In order to evaluate the performance of the algorithms proposed, they are compared, in terms of the quality of the solutions found, to other approaches

Algoritmos científicos

The Scientific Algorithms are a new metaheuristics inspired in the scientific research process. The new method introduces the idea of theme to search the solution space of hard problems. The inspiration for this class of algorithms comes from the act of researching that comprises thinking, knowledge sharing and disclosing new ideas. The ideas of the new method are illustrated in the Traveling Salesman Problem. A computational experiment applies the proposed approach to a new variant of the Traveling Salesman Problem named Car Renter Salesman Problem. The results are compared to state-of-the-art algorithms for the latter problem

Algoritmo treansgenético na solução do problema do Caixeiro Viajante

The Traveling Purchaser Problem is a variant of the Traveling Salesman Problem, where there is a set of markets and a set of products. Each product is available on a subset of markets and its unit cost depends on the market where it is available. The objective is to buy all the products, departing and returning to a domicile, at the least possible cost defined as the summation of the weights of the edges in the tour and the cost paid to acquire the products. A Transgenetic Algorithm, an evolutionary algorithm with basis on endosymbiosis, is applied to the Capacited and Uncapacited versions of this problem. Evolution in Transgenetic Algorithms is simulated with the interaction and information sharing between populations of individuals from distinct species. The computational results show that this is a very effective approach for the TPP regarding solution quality and runtime. Seventeen and nine new best results are presented for instances of the capacited and uncapacited versions, respectively

On the extended applications of Homogenous Balance Method

In this paper, we study the travelling wave reductions for certain (2 + 1)- and (3 + 1)-dimensional physically important nonlinear evolutionary equations by using the recently proposed Homogenous Balance Method (HBM). Through this analysis we explore certain new solutions for the equations we have studied. (C) 2001 Published by Elsevier B.V.

Parental care in the buffy-tufted-ear marmoset (Callithrix aurita) in wild and captive groups

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

O cenário nosológico de Goiás no século XIX

A província de Goiás gozava de uma situação sanitária ambígua, descrita simultaneamente como saudável e insalubre. Assim, este artigo apresenta diferentes versões sobre as condições nosológicas de Goiás, produzidas pelas autoridades locais, médicos, viajantes estrangeiros e expedições científicas.

An objective reconstruction of the chain of contagion

North's clustering method, which is based on a much used ecological model, the nearest neighbor distance, was applied to the objective reconstruction of the chain of household-to-household transmission of variola minor (the mild form of smallpox). The discrete within-household outbreaks were considered as points which were ordered in a time sequence using a 10-40 day interval between introduction of the disease into a source household and a receptor household. The closer points in the plane were assumed to have a larger probability of being links of a chain of household-to-household spread of the disease. The five defining distances (Manhattan or city-block distance between presumptive source and receptor dwellings) were 100, 200, 300, 400 and 500 m. The subchain sets obtained with the five defining distances were compared with the subchains empirically reconstructed during the field study of the epidemic through direct investigation of personal contacts of the introductory cases with either introductory or subsequent cases from previously affected households. The criteria of fit of theoretical to empirical clusters were: (a) the number of clustered dwellings and subchains, (b) number of dwellings in a subchain and (c) position of dwellings in a subchain. The defining distance closet to the empirical findings was 200 m, which fully agrees with the travelling habits of the study population. Less close but acceptable approximations were obtained with 100, 300, 400 and 500 m. The latter two distances gave identical results, as if a clustering ceiling had been reached. It seems that North's clustering model may be used for an objective reconstruction of the chain of contagious whose links are discrete within-household outbreaks. © 1984.

Problem of assignment cells to switches in a cellular mobile network via beam search method

The problem of assigning cells to switches in a cellular mobile network is an NP-hard optimization problem. So, real size mobile networks could not be solved by using exact methods. The alternative is the use of the heuristic methods, because they allow us to find a good quality solution in a quite satisfactory computational time. This paper proposes a Beam Search method to solve the problem of assignment cell in cellular mobile networks. Some modifications in this algorithm are also presented, which allows its parallel application. Computational results obtained from several tests confirm the effectiveness of this approach to provide good solutions for medium- and large-sized cellular mobile network.

Influence of nonsphericity of planetary satellites and perturbation of the third-body on the artificial satellites motion

Some orbital characteristics of lunar artificial satellites is presented taking into account the perturbation of the third-body in elliptical orbit and the non-uniform distribution of mass of the Moon. We consider the development of the non-sphericity of the Moon in zonal spherical harmonics up to the ninth order and sectorial harmonic C 22 due to the lunar equatorial ellipticity. The motion of the artificial satellite is studied under the single-averaged analytical model. The average is applied to the mean anomaly of the satellite to analyze low-altitude orbits which are of highest importance for future lunar missions. We found families of frozen orbits with long lifetimes for the problem of an orbiter travelling around the Moon.

Strategies to model scheduling decisions to plan the soft drink production process

In this paper we present a mixed integer model that integrates lot sizing and lot scheduling decisions for the production planning of a soft drink company. The main contribution of the paper is to present a model that differ from others in the literature for the constraints related to the scheduling decisions. The proposed strategy is compared to other strategies presented in the literature.

Modelagem matemática da doença do caranguejo letárgico via ondas viajantes

Pós-graduação em Biometria - IBB