Utilização de soluções business-to-business (B2B) no segmento downstream da cadeia de suprimentos de uma distribuidora de combustíveis

The pursuit of competitive advantage is lobbying organizations to strategically plan the use of their material, human, technological and financial resources, so that it s possible to add value to the product, even when it is considered a commodity. The scenario for this planning should not be limited to the company in question, but cover an entire supply chain, which is composed of several organizations which have common goals of growth and sustainability of the market. They should form trade links, integrating the chains of individual values, in a perspective of value system. In this supply chain there is a flow of services, payments and information, as products well as. The training of these links can be supported by the adoption of a set of information technology, here called solutions business-to-business (B2B), which will be responsible for the production, storage and distribution of relevant information to business transactions between the companies involved. On this view, this thesis aims to describe the B2B solutions adopted in the downstream segment of the supply chain of a distributor of fuel and the nature of these technologies as well as their impact on the creation of value for business and optimization of the relationship between companies. This is a case study on a national distributor of fuels, from a model of research produced under the influence of theories of integrated logistics system and value of Michael Porter. The analyses came to the conclusion that information technology is perceived as an essential tool to the operation of all activities carried out by the company. Among them, at was also brought the key activities of integrated logistics: administration of applications, inventory management, management transport and customer services, which were highlighted in this study. It was also noticed that even these activities are, in principle, purely operational; they all had in the adoption of strategies for leadership in cost or differentiation, supported by B2B solutions identified, making it more conducive to business and direct customer, the clinic reseller of fuel, to obtain value and benefits of this market segment as competitive

Algoritmo evolutivo paralelo para o problema de atribuição de localidades a anéis em redes sonet/sdh

The telecommunications play a fundamental role in the contemporary society, having as one of its main roles to give people the possibility to connect them and integrate them into society in which they operate and, therewith, accelerate development through knowledge. But as new technologies are introduced on the market, increases the demand for new products and services that depend on the infrastructure offered, making the problems of planning of telecommunication networks become increasingly large and complex. Many of these problems, however, can be formulated as combinatorial optimization models, and the use of heuristic algorithms can help solve these issues in the planning phase. This paper proposes the development of a Parallel Evolutionary Algorithm to be applied to telecommunications problem known in the literature as SONET Ring Assignment Problem SRAP. This problem is the class NP-hard and arises during the physical planning of a telecommunication network and consists of determining the connections between locations (customers), satisfying a series of constrains of the lowest possible cost. Experimental results illustrate the effectiveness of the Evolutionary Algorithm parallel, over other methods, to obtain solutions that are either optimal or very close to it

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.

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

Ajuste automático e otimização do tempo de espera (Idle time) em bombeio mecânico de petróleo

The present work presents an algorithm proposal, which aims for controlling and improving idle time to be applied in oil production wells equipped with beam pump. The algorithm was totally designed based on existing papers and data acquired from two Potiguar Basin pilot wells. Oil engineering concepts such as submergence, pump off, Basic Sediments and Water (BSW), Inflow Performance Relationship (IPR), reservo ir pressure, inflow pressure, among others, were included into the algorithm through a mathematical treatment developed from a typical well and then extended to the general cases. The optimization will increase the well production potential maximum utilization having the smallest number of pumping unit cycles directly reflecting on operational cost and electricity consumption reduction

Otimização de Algoritmos Criptográficos para Redes de Sensores e Atuadores Sem-fio para Poços do Tipo Plunger Lift

Wireless sensors and actuators Networks specified by IEEE 802.15.4, are becoming increasingly being applied to instrumentation, as in instrumentation of oil wells with completion Plunger Lift type. Due to specific characteristics of the environment being installed, it s find the risk of compromising network security, and presenting several attack scenarios and the potential damage from them. It`s found the need for a more detailed security study of these networks, which calls for use of encryption algorithms, like AES-128 bits and RC6. So then it was implement the algorithms RC6 and AES-128, in an 8 bits microcontroller, and study its performance characteristics, critical for embedded applications. From these results it was developed a Hybrid Algorithm Cryptographic, ACH, which showed intermediate characteristics between the AES and RC6, more appropriate for use in applications with limitations of power consumption and memory. Also was present a comparative study of quality of security among the three algorithms, proving ACH cryptographic capability.

Otimização de um sistema de distribuição predial de água fria: estudo de caso

This dissertation presents a methodology to the optimization of a predial system of cold water distribution. It s about a study of a case applied to the Tropical Buzios Residential Condominium, located in the Búzio s Beach, Nísia Floresta city, the east coast of the Rio Grande do Norte state, twenty kilometers far from Natal. The design of cold water distribution networks according to Norm NBR 5626 of the ABNT - Brazilian Association of Techniques Norms, does not guarantee that the joined solution is the optimal solution of less cost. It s necessary the use of an optimization methodology, that supplies us, between all the possible solutions, the minimum cost solution. In the optimization process of the predial system of water distribution of the Tropical Búzios Condominium, is used Method Granados, that is an iterative algorithm of optimization, based on the Dynamic Programming, that supplies the minimum cost s network, in function of the piezometric quota of the reservoir. For the application of this Method in ramifies networks, is used a program of computer in C language. This process is divided in two stages: attainment of the previous solution and reduction of the piezometric quota of headboard. In the attainment of the previous solution, the minors possible diameters are used that guarantee the limit of maximum speed and the requirements of minimum pressures. The piezometric quota of headboard is raised to guarantee these requirements. In the second stage of the Granados Method, an iterative process is used and it objective is to reduce the quota of headboard gradually, considering the substitution of stretches of the network pipes for the subsequent diameters, considering a minimum addition of the network cost. The diameter change is made in the optimal stretch that presents the lesser Exchange Gradient. The process is locked up when the headboard quota of desired is reached. The optimized network s material costs are calculated, and is made the analysis of the same ones, through the comparison with the conventional network s costs

Aplicaçaõ das técnicas Path-relinking e Vocabulary buiding na melhoria de performance do algoritmo memético para o problema do caixeiro viajante assimétrico

The present essay shows strategies of improvement in a well succeded evolutionary metaheuristic to solve the Asymmetric Traveling Salesman Problem. Such steps consist in a Memetic Algorithm projected mainly to this problem. Basically this improvement applied optimizing techniques known as Path-Relinking and Vocabulary Building. Furthermore, this last one has being used in two different ways, in order to evaluate the effects of the improvement on the evolutionary metaheuristic. These methods were implemented in C++ code and the experiments were done under instances at TSPLIB library, being possible to observe that the procedures purposed reached success on the tests done

Uma estratégia aleatória chamada de MOSES

This paper we study a random strategy called MOSES, which was introduced in 1996 by Fran¸cois. Asymptotic results of this strategy; behavior of the stationary distributions of the chain associated to strategy, were derived by Fran¸cois, in 1998, of the theory of Freidlin and Wentzell [8]. Detailings of these results are in this work. Moreover, we noted that an alternative approach the convergence of this strategy is possible without making use of theory of Freidlin and Wentzell, yielding the visit almost certain of the strategy to uniform populations which contain the minimum. Some simulations in Matlab are presented in this work

Otimização em comitês de classificadores: uma abordagem baseada em filtro para seleção de subconjuntos de atributos

Traditional applications of feature selection in areas such as data mining, machine learning and pattern recognition aim to improve the accuracy and to reduce the computational cost of the model. It is done through the removal of redundant, irrelevant or noisy data, finding a representative subset of data that reduces its dimensionality without loss of performance. With the development of research in ensemble of classifiers and the verification that this type of model has better performance than the individual models, if the base classifiers are diverse, comes a new field of application to the research of feature selection. In this new field, it is desired to find diverse subsets of features for the construction of base classifiers for the ensemble systems. This work proposes an approach that maximizes the diversity of the ensembles by selecting subsets of features using a model independent of the learning algorithm and with low computational cost. This is done using bio-inspired metaheuristics with evaluation filter-based criteria

Um estudo algorítmico para otimização do plano de tratamento da radioterapia conformal

This work performs an algorithmic study of optimization of a conformal radiotherapy plan treatment. Initially we show: an overview about cancer, radiotherapy and the physics of interaction of ionizing radiation with matery. A proposal for optimization of a plan of treatment in radiotherapy is developed in a systematic way. We show the paradigm of multicriteria problem, the concept of Pareto optimum and Pareto dominance. A generic optimization model for radioterapic treatment is proposed. We construct the input of the model, estimate the dose given by the radiation using the dose matrix, and show the objective function for the model. The complexity of optimization models in radiotherapy treatment is typically NP which justifyis the use of heuristic methods. We propose three distinct methods: MOGA, MOSA e MOTS. The project of these three metaheuristic procedures is shown. For each procedures follows: a brief motivation, the algorithm itself and the method for tuning its parameters. The three method are applied to a concrete case and we confront their performances. Finally it is analyzed for each method: the quality of the Pareto sets, some solutions and the respective Pareto curves

Algoritomos transgenéticos aplicados ao problema da árvore geradora biobjetivo

The Multiobjective Spanning Tree is a NP-hard Combinatorial Optimization problem whose application arises in several areas, especially networks design. In this work, we propose a solution to the biobjective version of the problem through a Transgenetic Algorithm named ATIS-NP. The Computational Transgenetic is a metaheuristic technique from Evolutionary Computation whose inspiration relies in the conception of cooperation (and not competition) as the factor of main influence to evolution. The algorithm outlined is the evolution of a work that has already yielded two other transgenetic algorithms. In this sense, the algorithms previously developed are also presented. This research also comprises an experimental analysis with the aim of obtaining information related to the performance of ATIS-NP when compared to other approaches. Thus, ATIS-NP is compared to the algorithms previously implemented and to other transgenetic already presented for the problem under consideration. The computational experiments also address the comparison to two recent approaches from literature that present good results, a GRASP and a genetic algorithms. The efficiency of the method described is evaluated with basis in metrics of solution quality and computational time spent. Considering the problem is within the context of Multiobjective Optimization, quality indicators are adopted to infer the criteria of solution quality. Statistical tests evaluate the significance of results obtained from computational experiments

Análise das medidas de boa e má diversidade na construção de comitês de classificadores através de metaheurísticas de otimização multiobjetivo

Committees of classifiers may be used to improve the accuracy of classification systems, in other words, different classifiers used to solve the same problem can be combined for creating a system of greater accuracy, called committees of classifiers. To that this to succeed is necessary that the classifiers make mistakes on different objects of the problem so that the errors of a classifier are ignored by the others correct classifiers when applying the method of combination of the committee. The characteristic of classifiers of err on different objects is called diversity. However, most measures of diversity could not describe this importance. Recently, were proposed two measures of the diversity (good and bad diversity) with the aim of helping to generate more accurate committees. This paper performs an experimental analysis of these measures applied directly on the building of the committees of classifiers. The method of construction adopted is modeled as a search problem by the set of characteristics of the databases of the problem and the best set of committee members in order to find the committee of classifiers to produce the most accurate classification. This problem is solved by metaheuristic optimization techniques, in their mono and multi-objective versions. Analyzes are performed to verify if use or add the measures of good diversity and bad diversity in the optimization objectives creates more accurate committees. Thus, the contribution of this study is to determine whether the measures of good diversity and bad diversity can be used in mono-objective and multi-objective optimization techniques as optimization objectives for building committees of classifiers more accurate than those built by the same process, but using only the accuracy classification as objective of optimization

Estimador do Tipo Núcleo para Densidades Limites de Cadeias de Markov com Espaço de Estados Geral

In this work we studied the consistency for a class of kernel estimates of f f (.) in the Markov chains with general state space E C Rd case. This study is divided into two parts: In the first one f (.) is a stationary density of the chain, and in the second one f (x) v (dx) is the limit distribution of a geometrically ergodic chain

Ergodicidade em cadeias de Markov não-homogêneas e cadeias de Markov com transições raras

The central objective of a study Non-Homogeneous Markov Chains is the concept of weak and strong ergodicity. A chain is weak ergodic if the dependence on the initial distribution vanishes with time, and it is strong ergodic if it is weak ergodic and converges in distribution. Most theoretical results on strong ergodicity assume some knowledge of the limit behavior of the stationary distributions. In this work, we collect some general results on weak and strong ergodicity for chains with space enumerable states, and also study the asymptotic behavior of the stationary distributions of a particular type of Markov Chains with finite state space, called Markov Chains with Rare Transitions