Gestão ambiental: um estudo sobre a percepção do problema da desertificação no Estado do Rio Grande do Norte

The objective of this study was to investigate the environmental perception of: People with common-sense knowledge on the desertification process in RN. People with scientific knowledge on the desertification process in RN. Focal points in the combat at desertification of the RN and public ministery representant with actions in interinstitutional articulations promoter (and/or relative actions) at the desertification process in the RN. The research was carried in the city of Natal-RN and in two small cities of the Seridó region (RN): Caicó and Currais Novos. The research carried, is classified as exploratory and 22 people were interviewed. The research includes: The propension/intensity of the desertification in the RN and in the Seridó region; Evaluation of the knowledge of those interviewed, concerning the subject desertification ; Problems in order to combat desertification; Causes of desertification; The profile of the interviewed. The results of this present study indicate that the a desertification process is more agressive in the Seridó region than in the state of RN, being the two following: the absence of preocupation of the affected population with the process and the escarcity of governamental recurses, indicates how problems greather in the combat to the phenomen. Decreasing of produtivity in the agriculture and increasing of the migration to the urbans centers have been the main consequences of the process, that have at water scarcity, deforestation and extraction of argil (being this, regional factor), relevant variables in the influence to the surgiment of the desertification process of the RN

Um algoritmo híbrido para o problema de roteamento de veículos com frotas heterogêneas

This paper aims to propose a hybrid meta-heuristics for the Heterogeneous Fleet Vehicle Routing Problem (HVRP), which is a combinatorial optimization problem NP-hard, and is characterized by the use of a limited fleet consists of different vehicles with different capacities. The hybrid method developed makes use of a memetic algorithm associated with the component optimizer Vocabulary Building. The resulting hybrid meta-heuristic was implemented in the programming language C + + and computational experiments generated good results in relation to meta-heuristic applied in isolation, proving the efficiency of the proposed method.

Metaheurísticas evolutivas para o problema de roteamento de unidades móveis de pistoneio

This paper presents metaheuristic strategies based on the framework of evolutionary algorithms (Genetic and Memetic) with the addition of Technical Vocabulary Building for solving the Problem of Optimizing the Use of Multiple Mobile Units Recovery of Oil (MRO units). Because it is an NP-hard problem, a mathematical model is formulated for the problem, allowing the construction of test instances that are used to validate the evolutionary metaheuristics developed

Uma abordagem híbrida para o problema de seleção de fornecedores em cadeia de suprimentos

This work presents a hybrid approach for the supplier selection problem in Supply Chain Management. We joined decision-making philosophy by researchers from business school and researchers from engineering in order to deal with the problem more extensively. We utilized traditional multicriteria decision-making methods, like AHP and TOPSIS, in order to evaluate alternatives according decision maker s preferences. The both techiniques were modeled by using definitions from the Fuzzy Sets Theory to deal with imprecise data. Additionally, we proposed a multiobjetive GRASP algorithm to perform an order allocation procedure between all pre-selected alternatives. These alternatives must to be pre-qualified on the basis of the AHP and TOPSIS methods before entering the LCR. Our allocation procedure has presented low CPU times for five pseudorandom instances, containing up to 1000 alternatives, as well as good values for all considered objectives. This way, we consider the proposed model as appropriate to solve the supplier selection problem in the SCM context. It can be used to help decision makers in reducing lead times, cost and risks in their supply chain. The proposed model can also improve firm s efficiency in relation to business strategies, according decision makers, even when a large number of alternatives must be considered, differently from classical models in purchasing literature

Algoritmos para o problema de localização de uma facilidade com distâncias limitadas e restrições de atendimento

The objective in the facility location problem with limited distances is to minimize the sum of distance functions from the facility to the customers, but with a limit on each distance, after which the corresponding function becomes constant. The problem has applications in situations where the service provided by the facility is insensitive after a given threshold distance (eg. fire station location). In this work, we propose a global optimization algorithm for the case in which there are lower and upper limits on the numbers of customers that can be served

Desenvolvimento de um modelo computacional para a ampliação do atendimento do Programa de Acessibilidade Especial Porta a Porta - PRAE

Worldwide, the demand for transportation services for persons with disabilities, the elderly, and persons with reduced mobility have increased in recent years. The population is aging, governments need to adapt to this reality, and this fact could mean business opportunities for companies. Within this context is inserted the Programa de Acessibilidade Especial porta a porta PRAE, a door to door public transportation service from the city of Natal-RN in Brazil. The research presented in this dissertation seeks to develop a programming model which can assist the process of decision making of managers of the shuttle. To that end, it was created an algorithm based on methods of generating approximate solutions known as heuristics. The purpose of the model is to increase the number of people served by the PRAE, given the available fleet, generating optimized schedules routes. The PRAE is a problem of vehicle routing and scheduling of dial-a-ride - DARP, the most complex type among the routing problems. The validation of the method of resolution was made by comparing the results derived by the model and the currently programming method. It is expected that the model is able to increase the current capacity of the service requests of transport

Algoritmo memético com infecção viral: uma aplicação ao problema do caixeiro viajante assimétrico

The Combinatorial Optimization is a basic area to companies who look for competitive advantages in the diverse productive sectors and the Assimetric Travelling Salesman Problem, which one classifies as one of the most important problems of this area, for being a problem of the NP-hard class and for possessing diverse practical applications, has increased interest of researchers in the development of metaheuristics each more efficient to assist in its resolution, as it is the case of Memetic Algorithms, which is a evolutionary algorithms that it is used of the genetic operation in combination with a local search procedure. This work explores the technique of Viral Infection in one Memetic Algorithms where the infection substitutes the mutation operator for obtaining a fast evolution or extinguishing of species (KANOH et al, 1996) providing a form of acceleration and improvement of the solution . For this it developed four variants of Viral Infection applied in the Memetic Algorithms for resolution of the Assimetric Travelling Salesman Problem where the agent and the virus pass for a symbiosis process which favored the attainment of a hybrid evolutionary algorithms and computational viable

Metodologia estatística na solução do problema do caixeiro viajante e na avaliação de algoritmos : um estudo aplicado à transgenética computacional

The problems of combinatory optimization have involved a large number of researchers in search of approximative solutions for them, since it is generally accepted that they are unsolvable in polynomial time. Initially, these solutions were focused on heuristics. Currently, metaheuristics are used more for this task, especially those based on evolutionary algorithms. The two main contributions of this work are: the creation of what is called an -Operon- heuristic, for the construction of the information chains necessary for the implementation of transgenetic (evolutionary) algorithms, mainly using statistical methodology - the Cluster Analysis and the Principal Component Analysis; and the utilization of statistical analyses that are adequate for the evaluation of the performance of the algorithms that are developed to solve these problems. The aim of the Operon is to construct good quality dynamic information chains to promote an -intelligent- search in the space of solutions. The Traveling Salesman Problem (TSP) is intended for applications based on a transgenetic algorithmic known as ProtoG. A strategy is also proposed for the renovation of part of the chromosome population indicated by adopting a minimum limit in the coefficient of variation of the adequation function of the individuals, with calculations based on the population. Statistical methodology is used for the evaluation of the performance of four algorithms, as follows: the proposed ProtoG, two memetic algorithms and a Simulated Annealing algorithm. Three performance analyses of these algorithms are proposed. The first is accomplished through the Logistic Regression, based on the probability of finding an optimal solution for a TSP instance by the algorithm being tested. The second is accomplished through Survival Analysis, based on a probability of the time observed for its execution until an optimal solution is achieved. The third is accomplished by means of a non-parametric Analysis of Variance, considering the Percent Error of the Solution (PES) obtained by the percentage in which the solution found exceeds the best solution available in the literature. Six experiments have been conducted applied to sixty-one instances of Euclidean TSP with sizes of up to 1,655 cities. The first two experiments deal with the adjustments of four parameters used in the ProtoG algorithm in an attempt to improve its performance. The last four have been undertaken to evaluate the performance of the ProtoG in comparison to the three algorithms adopted. For these sixty-one instances, it has been concluded on the grounds of statistical tests that there is evidence that the ProtoG performs better than these three algorithms in fifty instances. In addition, for the thirty-six instances considered in the last three trials in which the performance of the algorithms was evaluated through PES, it was observed that the PES average obtained with the ProtoG was less than 1% in almost half of these instances, having reached the greatest average for one instance of 1,173 cities, with an PES average equal to 3.52%. Therefore, the ProtoG can be considered a competitive algorithm for solving the TSP, since it is not rare in the literature find PESs averages greater than 10% to be reported for instances of this size.

Agentes Inteligentes com Foco de Atenção Afetivo em Simulações Baseadas em Agentes

Simulations based on cognitively rich agents can become a very intensive computing task, especially when the simulated environment represents a complex system. This situation becomes worse when time constraints are present. This kind of simulations would benefit from a mechanism that improves the way agents perceive and react to changes in these types of environments. In other worlds, an approach to improve the efficiency (performance and accuracy) in the decision process of autonomous agents in a simulation would be useful. In complex environments, and full of variables, it is possible that not every information available to the agent is necessary for its decision-making process, depending indeed, on the task being performed. Then, the agent would need to filter the coming perceptions in the same as we do with our attentions focus. By using a focus of attention, only the information that really matters to the agent running context are perceived (cognitively processed), which can improve the decision making process. The architecture proposed herein presents a structure for cognitive agents divided into two parts: 1) the main part contains the reasoning / planning process, knowledge and affective state of the agent, and 2) a set of behaviors that are triggered by planning in order to achieve the agent s goals. Each of these behaviors has a runtime dynamically adjustable focus of attention, adjusted according to the variation of the agent s affective state. The focus of each behavior is divided into a qualitative focus, which is responsible for the quality of the perceived data, and a quantitative focus, which is responsible for the quantity of the perceived data. Thus, the behavior will be able to filter the information sent by the agent sensors, and build a list of perceived elements containing only the information necessary to the agent, according to the context of the behavior that is currently running. Based on the human attention focus, the agent is also dotted of a affective state. The agent s affective state is based on theories of human emotion, mood and personality. This model serves as a basis for the mechanism of continuous adjustment of the agent s attention focus, both the qualitative and the quantative focus. With this mechanism, the agent can adjust its focus of attention during the execution of the behavior, in order to become more efficient in the face of environmental changes. The proposed architecture can be used in a very flexibly way. The focus of attention can work in a fixed way (neither the qualitative focus nor the quantitaive focus one changes), as well as using different combinations for the qualitative and quantitative foci variation. The architecture was built on a platform for BDI agents, but its design allows it to be used in any other type of agents, since the implementation is made only in the perception level layer of the agent. In order to evaluate the contribution proposed in this work, an extensive series of experiments were conducted on an agent-based simulation over a fire-growing scenario. In the simulations, the agents using the architecture proposed in this work are compared with similar agents (with the same reasoning model), but able to process all the information sent by the environment. Intuitively, it is expected that the omniscient agent would be more efficient, since they can handle all the possible option before taking a decision. However, the experiments showed that attention-focus based agents can be as efficient as the omniscient ones, with the advantage of being able to solve the same problems in a significantly reduced time. Thus, the experiments indicate the efficiency of the proposed architecture

Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço

The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to generate solutions that are close to the optimal, without the guarantee of finding the global optimum. Motivated by the difficulties in the resolution of these problems, this work proposes the development of parallel hybrid methods using the reinforcement learning, the metaheuristics GRASP and Genetic Algorithms. With the use of these techniques, we aim to contribute to improved efficiency in obtaining efficient solutions. In this case, instead of using the Q-learning algorithm by reinforcement learning, just as a technique for generating the initial solutions of metaheuristics, we use it in a cooperative and competitive approach with the Genetic Algorithm and GRASP, in an parallel implementation. In this context, was possible to verify that the implementations in this study showed satisfactory results, in both strategies, that is, in cooperation and competition between them and the cooperation and competition between groups. In some instances were found the global optimum, in others theses implementations reach close to it. In this sense was an analyze of the performance for this proposed approach was done and it shows a good performance on the requeriments that prove the efficiency and speedup (gain in speed with the parallel processing) of the implementations performed

Revisitando o problema de visibilidade para visualização tridimensional

We revisit the problem of visibility, which is to determine a set of primitives potentially visible in a set of geometry data represented by a data structure, such as a mesh of polygons or triangles, we propose a solution for speeding up the three-dimensional visualization processing in applications. We introduce a lean structure , in the sense of data abstraction and reduction, which can be used for online and interactive applications. The visibility problem is especially important in 3D visualization of scenes represented by large volumes of data, when it is not worthwhile keeping all polygons of the scene in memory. This implies a greater time spent in the rendering, or is even impossible to keep them all in huge volumes of data. In these cases, given a position and a direction of view, the main objective is to determine and load a minimum ammount of primitives (polygons) in the scene, to accelerate the rendering step. For this purpose, our algorithm performs cutting primitives (culling) using a hybrid paradigm based on three known techniques. The scene is divided into a cell grid, for each cell we associate the primitives that belong to them, and finally determined the set of primitives potentially visible. The novelty is the use of triangulation Ja 1 to create the subdivision grid. We chose this structure because of its relevant characteristics of adaptivity and algebrism (ease of calculations). The results show a substantial improvement over traditional methods when applied separately. The method introduced in this work can be used in devices with low or no dedicated processing power CPU, and also can be used to view data via the Internet, such as virtual museums applications

Uma contribuição à solução do problema dos k-servos usando aprendizagem por reforço

Neste trabalho é proposto um novo algoritmo online para o resolver o Problema dos k-Servos (PKS). O desempenho desta solução é comparado com o de outros algoritmos existentes na literatura, a saber, os algoritmos Harmonic e Work Function, que mostraram ser competitivos, tornando-os parâmetros de comparação significativos. Um algoritmo que apresente desempenho eficiente em relação aos mesmos tende a ser competitivo também, devendo, obviamente, se provar o referido fato. Tal prova, entretanto, foge aos objetivos do presente trabalho. O algoritmo apresentado para a solução do PKS é baseado em técnicas de aprendizagem por reforço. Para tanto, o problema foi modelado como um processo de decisão em múltiplas etapas, ao qual é aplicado o algoritmo Q-Learning, um dos métodos de solução mais populares para o estabelecimento de políticas ótimas neste tipo de problema de decisão. Entretanto, deve-se observar que a dimensão da estrutura de armazenamento utilizada pela aprendizagem por reforço para se obter a política ótima cresce em função do número de estados e de ações, que por sua vez é proporcional ao número n de nós e k de servos. Ao se analisar esse crescimento (matematicamente, ) percebe-se que o mesmo ocorre de maneira exponencial, limitando a aplicação do método a problemas de menor porte, onde o número de nós e de servos é reduzido. Este problema, denominado maldição da dimensionalidade, foi introduzido por Belmann e implica na impossibilidade de execução de um algoritmo para certas instâncias de um problema pelo esgotamento de recursos computacionais para obtenção de sua saída. De modo a evitar que a solução proposta, baseada exclusivamente na aprendizagem por reforço, seja restrita a aplicações de menor porte, propõe-se uma solução alternativa para problemas mais realistas, que envolvam um número maior de nós e de servos. Esta solução alternativa é hierarquizada e utiliza dois métodos de solução do PKS: a aprendizagem por reforço, aplicada a um número reduzido de nós obtidos a partir de um processo de agregação, e um método guloso, aplicado aos subconjuntos de nós resultantes do processo de agregação, onde o critério de escolha do agendamento dos servos é baseado na menor distância ao local de demanda

Avaliação cinética e potencial do Nb2O5 obtido a partir de um complexo de nióbio para formação do oleato de metila através da reação de esterificação do ácido oleico

Among the heterogeneous catalysts materials made from niobium show up as an alternative to meet the demand of catalysts for biodiesel production. This study aims to evaluate the potential of a heterogeneous catalyst derived from a complex of niobium in the reaction of methyl esterification of oleic acid. The catalyst was synthesized after calcination at different temperatures of a niobium complex ((NH4)3[NbO(C2O4)3].H2O) generating a niobium oxide nanostructure with a different commercial niobium oxide used to synthesize the complex. The commercial niobium oxide, the complex niobium and niobium catalyst were characterized by thermogravimetry (TG and DTA), surface area analysis (BET), scanning electron microscopy (SEM) and X-ray diffraction (XRD), showing the catalyst has researched morphological and crystallographic indicating a catalytic potential higher than that of commercial niobium oxide characteristics. Factorial with central composite design point, with three factors (calcination temperature, molar ratio of alcohol/oleic acid and mass percentage of catalyst) was performed. Noting that the optimal experimental point was given by the complex calcination temperature of 600°C, a molar ratio alcohol/oleic acid of 3.007/1 and the catalyst mass percentage of 7.998%, with a conversion of 22.44% oleic acid in methyl oleate to 60 min of reaction. We performed a composite linear and quadratic regression to determine an optimal statistical point of the reaction, the temperature of calcination of the complex at 450°C, the molar ratio of alcohol/oleic acid 3.3408/1 and mass percentage of catalyst of 7.6833% . Kinetic modeling to estimate parameters for heterogeneous catalysis it set well the experimental results with a final conversion of 85.01% with 42.38% of catalyst and without catalyst at 240 min reaction was performed. Allowing to evaluate the catalyst catalytic studied has the potential to be used in biodiesel production

Controle sanitário e ambiental de um projeto de reúso em um complexo de prédios corporativos

The study that resulted in this dissertation was developed at OU RNCE PETROBRAS, in Natal, which implemented a project of rational use and reuse of water, including use of wastewater from a Sewage Treatment Plant (STP) already in place, diluted with water from own wells for irrigation of green area of the building complex corporate enterprise. Establish a methodology that can serve as guidelines for future projects controlled reuse of water like this was the objective of this research. Been proposed, implemented and evaluated three instruments of sanitary and environmental control: 1) adaptation of sewage treatment plant and quality control of the treated effluent 2) analysis of soil-nutrient interaction in the irrigated area, 3) knowledge of the local hydrogeology, especially with regard to the direction of flow of the aquifer and location of collection wells of Companhia de Águas e Esgotos do Rio Grande do Norte (CAERN) situated in the surroundings. These instruments have proven sufficient and appropriate to ensure the levels of sanitary and environmental control proposed and studied, which were: a) control of water quality off the STP and the output of the irrigation reservoir, b) control of water quality sub surface soil and assessment of progress on soil composition, c) assessment of water quality in the aquifer. For this, we must: 1) establishing the monitoring plan of the STP and its effluent quality sampling points and defining the parameters of analysis, improve the functioning of that identifying the adequacy of flow and screening as the main factors of operational control, and increase the efficiency of the station to a relatively low cost, using additional filters, 2) propose, implement and adapt simple collectors to assess the quality of water percolating into the soil of the irrigated area, 3) determine the direction of groundwater flow in the area study and select the wells for monitoring of the aquifer.

Uso do sensoriamento remoto orbital no monitoramento da dispersão de macrófitas nos reservatórios do complexo Tietê

A presença de algumas substâncias na água, como pigmentos fotossintetizantes, particulados, etc., afeta sua cor, provocando mudanças na radiância da água registrada por sensores orbitais. Nesse sentido, o sensoriamento remoto pode se constituir em uma fonte complementar de dados para o monitoramento da qualidade da água em grandes reservatórios (Novo et al., 1994). No contexto de um projeto de pesquisa realizado na AES Tietê S.A., com o objetivo de desenvolver técnicas para a avaliação da área com infestação de plantas aquáticas, imagens orbitais multiespectrais foram usadas tanto para mapear a dispersão espacial e estimar a área de ocorrência de macrófitas aquáticas, em duas épocas distintas, quanto para orientar a definição de pontos de amostragem in loco, visando a coleta e posterior análise da água e de sedimentos nos reservatórios. Este trabalho apresenta uma descrição do procedimento metodológico adotado na análise das imagens multiespectrais, bem como os resultados obtidos na caracterização dos reservatórios de Barra Bonita, Bariri, Ibitinga, Promissão e Nova Avanhandava, em termos de seu dimensionamento, variabilidade espectral da água e presença de macrófitas emersas, nas duas épocas do ano consideradas.