A robust controller design method for feedback substitution schemes using genetic algorithms

Controllers for feedback substitution schemes demonstrate a trade-off between noise power gain and normalized response time. Using as an example the design of a controller for a radiometric transduction process subjected to arbitrary noise power gain and robustness constraints, a Pareto-front of optimal controller solutions fulfilling a range of time-domain design objectives can be derived. In this work, we consider designs using a loop shaping design procedure (LSDP). The approach uses linear matrix inequalities to specify a range of objectives and a genetic algorithm (GA) to perform a multi-objective optimization for the controller weights (MOGA). A clonal selection algorithm is used to further provide a directed search of the GA towards the Pareto front. We demonstrate that with the proposed methodology, it is possible to design higher order controllers with superior performance in terms of response time, noise power gain and robustness.

Sustainable urban metabolism as a link between bio-physical sciences and urban planning: the BRIDGE project

Urban metabolism considers a city as a system with flows of energy and material between it and the environment. Recent advances in bio-physical sciences provide methods and models to estimate local scale energy, water, carbon and pollutant fluxes. However, good communication is required to provide this new knowledge and its implications to endusers (such as urban planners, architects and engineers). The FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) aimed to address this gap by illustrating the advantages of considering these issues in urban planning. The BRIDGE Decision Support System (DSS) aids the evaluation of the sustainability of urban planning interventions. The Multi Criteria Analysis approach adopted provides a method to cope with the complexity of urban metabolism. In consultation with targeted end-users, objectives were defined in relation to the interactions between the environmental elements (fluxes of energy, water, carbon and pollutants) and socioeconomic components (investment costs, housing, employment, etc.) of urban sustainability. The tool was tested in five case study cities: Helsinki, Athens, London, Florence and Gliwice; and sub-models were evaluated using flux data selected. This overview of the BRIDGE project covers the methods and tools used to measure and model the physical flows, the selected set of sustainability indicators, the methodological framework for evaluating urban planning alternatives and the resulting DSS prototype.

Sustainability assessment indicators and methodology for intelligent buildings

The sustainable intelligent building is a building that has the best combination of environmental, social, economic and technical values. And its sustainability assessment is related with system engineering methods and multi-criteria decision-making. Therefore firstly, the wireless monitoring system of sustainable parameters for intelligent buildings is achieved; secondly, the indicators and key issues based on the “whole life circle” for sustainability of intelligent buildings are researched; thirdly, the sustainable assessment model identified on the structure entropy and fuzzy analytic hierarchy process is proposed.

Cross-entropy optimizer: a new tool to study precession in astrophysical jets

Evidence of jet precession in many galactic and extragalactic sources has been reported in the literature. Much of this evidence is based on studies of the kinematics of the jet knots, which depends on the correct identification of the components to determine their respective proper motions and position angles on the plane of the sky. Identification problems related to fitting procedures, as well as observations poorly sampled in time, may influence the follow-up of the components in time, which consequently might contribute to a misinterpretation of the data. In order to deal with these limitations, we introduce a very powerful statistical tool to analyse jet precession: the cross-entropy method for continuous multi-extremal optimization. Only based on the raw data of the jet components (right ascension and declination offsets from the core), the cross-entropy method searches for the precession model parameters that better represent the data. In this work we present a large number of tests to validate this technique, using synthetic precessing jets built from a given set of precession parameters. With the aim of recovering these parameters, we applied the cross-entropy method to our precession model, varying exhaustively the quantities associated with the method. Our results have shown that even in the most challenging tests, the cross-entropy method was able to find the correct parameters within a 1 per cent level. Even for a non-precessing jet, our optimization method could point out successfully the lack of precession.

Solving the Vehicle Routing Problem with Genetic ALgorithm and Simulated Annealing

This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.

Evaluating And Optimizing Sustainable Drainage Design To Maximize Multiple Benefits: Case Studies In China

In the past, the focus of drainage design was on sizing pipes and storages in order to provide sufficient network capacity. This traditional approach, together with computer software and technical guidance, had been successful for many years. However, due to rapid population growth and urbanisation, the requirements of a “good” drainage design have also changed significantly. In addition to water management, other aspects such as environmental impacts, amenity values and carbon footprint have to be considered during the design process. Going forward, we need to address the key sustainability issues carefully and practically. The key challenge of moving from simple objectives (e.g. capacity and costs) to complicated objectives (e.g. capacity, flood risk, environment, amenity etc) is the difficulty to strike a balance between various objectives and to justify potential benefits and compromises. In order to assist decision makers, we developed a new decision support system for drainage design. The system consists of two main components – a multi-criteria evaluation framework for drainage systems and a multi-objective optimisation tool. The evaluation framework is used for the quantification of performance, life-cycle costs and benefits of different drainage systems. The optimisation tool can search for feasible combinations of design parameters such as the sizes, order and type of drainage components that maximise multiple benefits. In this paper, we will discuss real-world application of the decision support system. A number of case studies have been developed based on recent drainage projects in China. We will use the case studies to illustrate how the evaluation framework highlights and compares the pros and cons of various design options. We will also discuss how the design parameters can be optimised based on the preferences of decision makers. The work described here is the output of an EngD project funded by EPSRC and XP Solutions.

Utilização de uma sistemática de tomada de decisão para selecionar e priorizar um portfólio de projetos de investimento

Nos dias de hoje existe uma grande demanda e pressão na seleção e definição de prioridades das alternativas de investimento para alavancar o crescimento de longo prazo das empresas. Em paralelo a este cenário, o ambiente global está cada vez mais incerto, o que implica que as escolhas realizadas por estas empresas devem se adaptar aos novos desejos do mercado e, principalmente, devem manter o direcionamento de crescimento almejado pelas mesmas. Neste contexto conturbado, as ferramentas tradicionais utilizadas para a tomada de decisão, para selecionar e definir as prioridades são as análises econômico-financeira representadas pelo Valor Presente Líquido, a Taxa Interna de Retorno e o Payback. Apesar de estes itens serem métodos robustos e consistentes na avaliação de projetos de investimentos, eles focam apenas em um aspecto (o financeiro), e as empresas, atualmente, estão envolvidas em ambientes que precisam de uma abordagem mais ampla, contemplando outras visões e dimensões não presentes nos estudos financeiros. Ou seja, quando se faz uma análise de carteira de projetos alinhada ao planejamento estratégico, é necessário realizar uma abordagem multicritério envolvendo indicadores quantitativos e qualitativos e disponibilizando aos tomadores de decisão uma informação completa e padronizada de todos os projetos, uma vez que estas iniciativas não possuem características homogêneas, pois cada uma apresenta sua respectiva particularidade e, principalmente, está em diferentes estágios de maturidade. Aliado a estes pontos, é perceptível que o processo de seleção e priorização de projetos necessita de uma sistematização que garanta a esta decisão e a este Portfólio uma maior estabilidade e fidedignidade das informações. Neste trabalho, portanto, foi elaborada uma análise multivariada, mais especificamente, a utilização de sistemas de apoio à tomada de decisão. Foram escolhidos outros critérios além do econômico-financeiro, para suportar a seleção e priorização de projetos no atendimento dos objetivos estratégicos da organização e de seus stakeholders.

O valor da tecnologia da informação: considerações sobre a avaliação de investimentos estratégicos em TI e sobre o processo de análise e tomada de decisão

Este trabalho discute os principais fatores a serem considerados na tomada de decisões estratégicas relativas a investimentos em tecnologia da informação. É feita uma avaliação do impacto da implantação de TI nas organizações e são sugeridos métodos que podem ser utilizados para medir os benefícios tangíveis e intangíveis do investimento em TI. A seguir, é feita uma apresentação breve da teoria de análise de decisões e da forma como algumas das novas ferramentas de software podem auxiliar os seres humanos a tomar decisões racionais. Por fim, é apresentado um exemplo de um modelo multi-critérios simples (SMARTS) como uma ferramenta de apoio ao processo de decisão.

MCDA: análise de decisão multicritério como ferramenta de avaliação de instalações portuárias: o caso dos terminais de contêineres brasileiros

Este trabalho busca avaliar, com suporte da metodologia MCDA - análise de decisão multicritério, os terminais de contêineres brasileiros quanto a suas potencialidades como vetores de crescimento sustentado da economia, no médio e longo prazo, para priorização de investimentos públicos e privados. O trabalho se consubstancia em um levantamento bibliográfico do tema decisório, que lhe serve de base, seguido de um estudo do tema portuário, a fim de levantar os fatores que tornam viável o florescimento e desenvolvimento de um sítio portuário, além de buscar tendências do setor de contêineres no Brasil. Após estas etapas, foi desenvolvido uma modelagem para o problema de avaliação dos terminais, com ajuda do software Expert Choice. Os resultados obtidos apontam para uma alteração sensível de paradigma no panorama portuário nacional em um cenário futuro. Portos que hoje se localizam na parte superior da lista de movimentação de contêineres, à frente nas estatísticas, podem não ter para onde se expandir, enquanto outros, que se encontram menos pujantes, podem florescer nas próximas décadas, devido às características de cada sítio portuário. As mais relevantes foram selecionadas como critérios do modelo desenvolvido, são eles: águas abrigadas, retroáreas, acessos terrestres e marítimos, equacionamento de questões ambientais, localização estratégica, vocação regional, extensão de cais e áreas de expansão. Entre as conclusões deste estudo, pode-se citar: 1 - O Porto de Santos, tradicional líder do ranking nacional em movimentação de contêineres, deve se manter entre os primeiros, graças à sua proximidade com o principal centro econômico e industrial nacional, a região da grande São Paulo, embora esteja com sua capacidade perto do limite operacional, conta com áreas de expansão, como o projeto Barnabé-Bagres. 2 - Outro porto que se destacou na classificação final foi o de Itaguaí, já hoje com movimentação crescente e enorme potencial de crescimento na área de contêineres. Possui excelente condição de águas abrigadas, boa localização estratégica, entre Rio de Janeiro e São Paulo, dois pólos econômicos fortes, com influência decisiva no cenário nacional, e que dispõe de consistente plano de expansão, especialmente relacionado ao aumento de contêineres.

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