Modelagem da decisão por pacotes de viagem: um estudo usando processo de hierarquia analítica AHP

The objective of this dissertation is to propose a Multi Criteria Decision Aid Model to be used by the costumers of the travel agencies and help them to choose the best package travel. The main objective is to contribute for the simplification of the travel package decision choice from the identification of the models of values and preference of the customers and applying them to the existing package. It is used the Analytic Hierarchy Process (AHP) method to structuralize a decision hierarchic model composed by six criteria (package cost, hotel category, security of the city, travel time, direct flight and position in ranking of the 10 most visited destination) and five real alternatives of packages for a holiday of three days created from travel agency data. The decision analysis was realized for the choice of a travel package by a group composed by two couples that regularly travels together, to which was asked to do a pairwise judgment of the criteria and the alternatives. The mains results show that, although been a group that travels together, there are different models of values in the weights of the criteria and a certain convergence in the scales of preferences of the alternatives in the criteria. It was not pointed a dominant alternative for all the members of the group separately, but an analysis of a total utility of the group shows a classification and an order of the travel packages and an alternative clearly in front of the others. The sensitivity analysis revels that there are changes in the ranking, but the two alternatives best classified in the normal analysis are the same ones in the sensitivity analysis, although with the positions changed. The analysis also led to a simplification of the process with the exclusion of alternatives dominated for the others ones. As main conclusion, it is evaluated that the model and method suggested allow a simplification of the decision process in the choice of travel packages

Modelagem de decisão na seleção de equipamento: um estudo usando o processo analítico hierárquico na contratação de sondas de perfuração de poços de petróleo

The main goal of this dissertation is to develop a Multi Criteria Decision Aid Model to be used in Oils and Gas perforation rigs contracts choices. The developed model should permit the utilization of multiples criterions, covering problems that exist with models that mainly use the price of the contracts as its decision criterion. The AHP has been chosen because its large utilization, not only academic, but in many other areas, its simplicity of use and flexibility, and also fill all the requirements necessary to complete the task. The development of the model was conducted by interviews and surveys with one specialist in this specific area, who also acts as the main actor on the decision process. The final model consists in six criterions: Costs, mobility, automation, technical support, how fast the service could be concluded and availability to start the operations. Three rigs were chosen as possible solutions for the problem. The results reached by the utilizations of the model suggests that the utilization of AHP as a decision support system in this kind of situation is possible, allowing a simplifications of the problem, and also it s a useful tool to improve every one involved on the process s knowledge about the problem subject, and its possible solutions

Análise de critérios de decisão em estratégia de arranjos produtivos locais: um estudo aplicando o processo de hierarquia analítica (AHP) no setor de cerâmica

This master thesis has the objective of investigating the strategic decision criteria of participants of Local Production Arrangements (LPA) in Brazil. The LPA s are an initiative of support agents to enterprises with the purpose of organizing joint actions for the development of groups (clusters) of enterprises. The choice of the actions is a decision of the participating enterprises and this paper aims at applying a Multi-criteria Analysis Method to analyze the criteria of entrepreneurs that are participating of a LPA. The used method is the Process of Analytical Hierarchy (PAH) and an application is presented along with questionnaires to participants of a ceramic LPA in the northeast of Brazil. The main results show that, in first place, from the implicit strategy of each enterprise there is only one objective for the LPA group and so, at the beginning, an action decided by all of them tends to favor some more than others. In second place, it was observed that there are general inconsistencies between the strategic objectives and the importance as to criteria, even though there have been cases of coherency. As the main conclusion it is pointed that the use of Methods of MCDA is useful to improve the decision making process and to bring more transparency to the logic of the found results

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

Avaliação da produção de sedimento na bacia hidrográfica do rio Potengi através do modelo SWAT

Anthropic disturbances in watersheds, such as inappropriate building development, disorderly land occupation and unplanned land use, may strengthen the sediment yield and the inflow into the estuary, leading to siltation, changes in the reach channel conformation, and ecosystem/water quality problems. Faced with such context, this study aims to assess the applicability of SWAT model to estimate, even in a preliminary way, the sediment yield distribution along the Potengi River watershed, as well as its contribution to the estuary. Furthermore, an assessment of its erosion susceptibility was used for comparison. The susceptibility map was developed by overlaying rainfall erosivity, soil erodibility, the slope of the terrain and land cover. In order to overlap these maps, a multi-criteria analysis through AHP method was applied. The SWAT was run using a five year period (1997-2001), considering three different scenarios based on different sorts of human interference: a) agriculture; b) pasture; and c) no interference (background). Results were analyzed in terms of surface runoff, sediment yield and their propagation along each river section, so that it was possible to find that the regions in the extreme west of the watershed and in the downstream portions returned higher values of sediment yield, reaching respectively 2.8 e 5.1 ton/ha.year, whereas central areas, which were less susceptible, returned the lowest values, never more than 0.7 ton/ha.ano. It was also noticed that in the west sub-watersheds, where one can observe the headwaters, sediment yield was naturally forced by high declivity and weak soils. In another hand, results suggest that the eastern part would not contribute to the sediment inflow into the estuary in a significant way, and the larger part of the sediment yield in that place is due to anthropic activities. For the central region, the analysis of sediment propagation indicates deposition predominance in opposition to transport. Thus, it s not expected that isolated rain storms occurring in the upstream river portions would significantly provide the estuary with sediment. Because the model calibration process hasn t been done yet, it becomes essential to emphasize that values presented here as results should not be applied for pratical aims. Even so, this work warns about the risks of a growth in the alteration of natural land cover, mainly in areas closer to the headwaters and in the downstream Potengi River

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

Algoritmos experimentais para o problema biobjetivo da árvore geradora quadrática em adjacência de arestas

The Quadratic Minimum Spanning Tree (QMST) problem is a generalization of the Minimum Spanning Tree problem in which, beyond linear costs associated to each edge, quadratic costs associated to each pair of edges must be considered. The quadratic costs are due to interaction costs between the edges. When interactions occur between adjacent edges only, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). Both QMST and AQMST are NP-hard and model a number of real world applications involving infrastructure networks design. Linear and quadratic costs are summed in the mono-objective versions of the problems. However, real world applications often deal with conflicting objectives. In those cases, considering linear and quadratic costs separately is more appropriate and multi-objective optimization provides a more realistic modelling. Exact and heuristic algorithms are investigated in this work for the Bi-objective Adjacent Only Quadratic Spanning Tree Problem. The following techniques are proposed: backtracking, branch-and-bound, Pareto Local Search, Greedy Randomized Adaptive Search Procedure, Simulated Annealing, NSGA-II, Transgenetic Algorithm, Particle Swarm Optimization and a hybridization of the Transgenetic Algorithm with the MOEA-D technique. Pareto compliant quality indicators are used to compare the algorithms on a set of benchmark instances proposed in literature.

Algoritmos experimentais para o problema biobjetivo da árvore geradora quadrática em adjacência de arestas

The Quadratic Minimum Spanning Tree (QMST) problem is a generalization of the Minimum Spanning Tree problem in which, beyond linear costs associated to each edge, quadratic costs associated to each pair of edges must be considered. The quadratic costs are due to interaction costs between the edges. When interactions occur between adjacent edges only, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). Both QMST and AQMST are NP-hard and model a number of real world applications involving infrastructure networks design. Linear and quadratic costs are summed in the mono-objective versions of the problems. However, real world applications often deal with conflicting objectives. In those cases, considering linear and quadratic costs separately is more appropriate and multi-objective optimization provides a more realistic modelling. Exact and heuristic algorithms are investigated in this work for the Bi-objective Adjacent Only Quadratic Spanning Tree Problem. The following techniques are proposed: backtracking, branch-and-bound, Pareto Local Search, Greedy Randomized Adaptive Search Procedure, Simulated Annealing, NSGA-II, Transgenetic Algorithm, Particle Swarm Optimization and a hybridization of the Transgenetic Algorithm with the MOEA-D technique. Pareto compliant quality indicators are used to compare the algorithms on a set of benchmark instances proposed in literature.