Multipath policy routing in packet switched networks

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Business model analysis of Mobitto: How to solve the chicken and egg problem of a multi-sided platform?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Uncertainty, generalization, and neural representation of relevant variables for decision making

Dissertation presented to obtain the Ph.D degree in Biology, Computational Biology.

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

Snakebites as a largely neglected problem in the Brazilian Amazon: highlights of the epidemiological trends in the State of Amazonas

Envenoming snakebites are thought to be a particularly important threat to public health worldwide, especially in rural areas of tropical and subtropical countries. The true magnitude of the public health threat posed by snakebites is unknown, making it difficult for public health officials to optimize prevention and treatment. The objective of this work was to conduct a systematic review of the literature to gather data on snakebite epidemiology in the Amazon region and describe a case series of snakebites from epidemiological surveillance in the State of Amazonas (1974-2012). Only 11 articles regarding snakebites were found. In the State of Amazonas, information regarding incidents involving snakes is scarce. Historical trends show an increasing number of cases after the second half of the 1980s. Snakebites predominated among adults (20-39 years old; 38%), in the male gender (78.9%) and in those living in rural areas (85.6%). The predominant snake envenomation type was bothropic. The incidence reported by the epidemiological surveillance in the State of Amazonas, reaching up to 200 cases/100,000 inhabitants in some areas, is among the highest annual snakebite incidence rates of any region in the world. The majority of the cases were reported in the rainy season with a case-fatality rate of 0.6%. Snakebite envenomation is a great disease burden in the State of Amazonas, representing a challenge for future investigations, including approaches to estimating incidence under-notification and case-fatality rates as well as the factors related to severity and disabilities.

The effect of deforestation on the water cycle in the amazon basin: an attempt reformulate the problem

If widespread deforestation in Amazon results in reduced evaporative water flux, then either a decrease in evaporation is compensated locally by reduced rainfall,or else changed moisture balance expresses itself downwind in the yet undisturbed forest. The question of where rain will occur is crucial. It is suggested that the appearance of clouds and the occurrence of rainout is governed primarily by the interplay of local meteorologic and physical geography parameters with the atmospheric stability structure except for a few well-defined periods when rain is dominated by large scale atmospheric instability. This means that the study of these phenomena (local heat balances,studies on cloud formation mechanism, vertical atmospheric stability, etc.) must be made on the scale of the cloud size, a few tens of kilometers at most.

A multi-criteria decision support system for a routing problem in waste collection

Autor proof

The non-emergency patient transport modelled as a team orienteering problem

This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.

A decision support system for a waste collection vehicle routing problem

The selective collection of municipal solid waste for recycling is a very complex and expensive process, where a major issue is to perform cost-efficient waste collection routes. Despite the abundance of commercially available software for fleet management, they often lack the capability to deal properly with sequencing problems and dynamic revision of plans and schedules during process execution. Our approach to achieve better solutions for the waste collection process is to model it as a vehicle routing problem, more specifically as a team orienteering problem where capacity constraints on the vehicles are considered, as well as time windows for the waste collection points and for the vehicles. The final model is called capacitated team orienteering problem with double time windows (CTOPdTW).We developed a genetic algorithm to solve routing problems in waste collection modelled as a CTOPdTW. The results achieved suggest possible reductions of logistic costs in selective waste collection.

Decision methods applied to solve a safety problem on a waste treatment facility

To solve a health and safety problem on a waste treatment facility, different multicriteria decision methods were used, including the PROV Exponential decision method. Four alternatives and ten attributes were considered. We found a congruent solution, validated by the different methods. The AHP and the PROV Exponential decision method led us to the same options ordering, but the last method reinforced one of the options as being the best performing one, and detached the least performing option. Also, the ELECTRE I method results led to the same ordering which allowed to point the best solution with reasonable confidence. This paper demonstrates the potential of using multicriteria decision methods to support decision making on complex problems such as risk control and accidents prevention.

Relative information entropy in cosmology: The problem of information entanglement

The necessary information to distinguish a local inhomogeneous mass density field from its spatial average on a compact domain of the universe can be measured by relative information entropy. The Kullback-Leibler (KL) formula arises very naturally in this context, however, it provides a very complicated way to compute the mutual information between spatially separated but causally connected regions of the universe in a realistic, inhomogeneous model. To circumvent this issue, by considering a parametric extension of the KL measure, we develop a simple model to describe the mutual information which is entangled via the gravitational field equations. We show that the Tsallis relative entropy can be a good approximation in the case of small inhomogeneities, and for measuring the independent relative information inside the domain, we propose the R\'enyi relative entropy formula.

Comprensión en resolución de problemas en Física: niveles de representación e inferencias basadas en el conocimiento. Comprehension in Physics Problem-Solving: levels of representation and knowledge-based inferences.

Se propone desarrollar e integrar estudios sobre Modelado y Resolución de Problemas en Física que asumen como factores explicativos: características de la situación planteada, conocimiento de la persona que resuelve y proceso puesto en juego durante la resolución. Interesa comprender cómo los estudiantes acceden al conocimiento previo, qué procedimientos usan para recuperar algunos conocimientos y desechar otros, cuáles son los criterios que dan coherencia a sus decisiones, cómo se relacionan estas decisiones con algunas características de la tarea, entre otras. Todo ello con miras a estudiar relaciones causales entre las dificultades encontradas y el retraso o abandono en las carreras.Se propone organizar el trabajo en tres ejes, los dos primeros de construcción teórica y un tercero de implementación y transferencia. Se pretende.1.-Estudiar los procesos de construcción de las representaciones mentales en resolución de problemas de física, tanto en expertos como en estudiantes de diferentes niveles académicos.2.-Analizar y clasificar las inferencias que se producen durante las tareas de comprensión en resolución de problemas de física. Asociar dichas inferencias con procesos de transición entre representaciones mentales de diferente naturaleza.3.-Desarrollar materiales y diseños instruccionales en la enseñanza de la Física, fundamentado en un conocimiento de los requerimientos psicológicos de los estudiantes en diversas tareas de aprendizaje.En términos generales se plantea un enfoque interpretativo a la luz de marcos de la psicología cognitiva y de los desarrollos propios del grupo. Se trabajará con muestras intencionales de alumnos y profesores de física. Se utilizarán protocolos verbales y registros escritos producidos durante la ejecución de las tareas con el fin de identificar indicadores de comprensión, inferencias, y diferentes niveles de representación. Se prevé analizar material escrito de circulación corriente sea comercial o preparado por los docentes de las carreras involucradas.Las características del objeto de estudio y el distinto nivel de desarrollo en que se encuentran los diferentes ojetivos específicos llevan a que el abordaje contemple -según consideracion de Juni y Urbano (2006)- tanto la lógica cualitativa como la cuantitativa.