Many real-world problems could be formulated in a way to fit the necessary form for discrete optimization. Discrete optimization problems can be solved by numerous different techniques that have developed over time. Some of the techniques provide optimal solution(s) to the problem and some of them give "good enough" solution(s). The fundamental reason for developing techniques capable of producing solutions that are not necessarily optimal is the fact that many discrete optimization problems are NP-complete. Metaheuristic algorithms are a common name for a set of general-purpose techniques developed to provide solution(s) to the problems associated with discrete optimization. Mostly the techniques are based on natural metaphors. Discrete optimization could be applied to countless problems in transportation engineering. Recently, researchers started studying the behavior of social insects (ants) in an attempt to use the swarm intelligence concept to develop artificial systems with the ability to search a problem's solution space in a way that is similar to the foraging search by a colony of social insects. The development of artificial systems does not entail the complete imitation of natural systems, but explores them in search of ideas for modeling. This research is partially devoted to the development of a new system based on the foraging behavior of bee colonies — Bee System. The Bee System was tested through many instances of the Traveling Salesman Problem. Many transportation-engineering problems, besides being of combinatorial nature, are characterized by uncertainty. In order to address these problems, the second part of the research is devoted to development of the algorithms that combine the existing results in the area of swarm intelligence (The Ant System) and approximate reasoning. The proposed approach — Fuzzy Ant System is tested on the following two examples: Stochastic Vehicle Routing Problem and Schedule Synchronization in Public Transit. / Ph. D.

Orientadores: Akebo Yamakami, Laecio Carvalho de Barros, Laercio Luis Vendite / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T04:11:06Z (GMT). No. of bitstreams: 1 Castanho_MariaJosedePaula_D.pdf: 5605275 bytes, checksum: 589180e36f1eeebf2b8fa1ced3a0a4db (MD5) Previous issue date: 2005 / Resumo: O câncer de próstata é, atualmente, o segundo tipo de câncer com maior incidência entre a população masculina, no Brasil. Estimar o seu estágio, com as informações clínicas disponíveis para decidir a terapia a ser aplicada, é uma tarefa árdua. Neste trabalho, um modelo matemático é elaborado para auxiliar o médico na tomada de decisão. A teoria dos conjuntosfuzzy, por sua capacidade em lidar com incertezas, inerentes aos conceitos médicos, é a ferramenta utilizada, não só para desenvolver o modelo, como também para desenvolver a metodologia para sua avaliação, baseada na análise ROC (Receiver Operating Characteristic). A avaliação foi feita utilizando-se dados obtidos junto ao Instituto Americano do Câncer e permite afinnar que o sistema especialista construí do discrimina pacientes com câncer confinado à próstata daqueles com câncer não-confinado. Considerando a taxa de crescimento como um parâmetro incerto e variável na população, também é apresentado um modelo para descrever o crescimento do tumor / Abstract: Nowadays, prostate cancer is the second most common man cancer diagnosed in Brazil. Predicting the cancer stage from available clinical information to decide the therapy to be used is hard work. ln this study a mathematical model is developed to assist the physician in this task. The fuzzy sets theory provides effective tools to handle and manipulate imprecise data and to make decisions based on such data. As imprecision is a characteristic of medical concepts, this theory is utilized not oniy to develop the model as to develop the methodology for its evaluation, based on ROC (Receiver Operating Characteristic) analysis. To evaluate its performance, data from the American Cancer lnstitute were used. The results indicate that the model is able to discriminate patients with organ-confined disease from those with non-confined cancer. In addition, considering the growth rate as an uncertain, changeable parameter in the population, a model to describe the tumor growth is suggested. / Doutorado / Automação / Doutor em Engenharia Elétrica

Advances in microprocessor and communications technologies are making it possible to deploy advanced traffic signal controllers capable of integrating emergency vehicle preemption and transit priority operations. However, investment planning for such an integrated system is not a trivial task. Investment planning for such a system requires a holistic approach that considers institutional, technical and financial issues from a systems perspective. Two distinct service providers, fire and rescue providers and transit operators, with separate operational functions, objectives, resources and constituents are involved. Performance parameters for the integrated system are not well defined and performance data are often imprecise in nature. Transportation planners and managers interested in deploying integrated emergency vehicle preemption and traffic priority systems do not have an evaluation approach or a common set of performance metrics to make an informed decision. There is a need for a simple structured analytical approach and tools to assess the impacts of an integrated emergency vehicle preemption and transit priority system as part of investment decision making processes. This need could be met with the assistance of a decision support system (DSS) developed to provide planners and managers a simple and intuitive analytical approach to assist in making investment decisions regarding emergency vehicle preemption and transit signal priority. This dissertation has two research goals: (1) to develop a decision support system framework to assess the impacts of advanced traffic signal control systems capable of integrating emergency vehicle preemption and transit signal priority operations for investment planning purposes; and (2) to develop selected analytical tools for incorporation into the decision support system framework. These analytical tools will employ fuzzy sets theory concepts, as well as cost and accident reduction factors. As part of this research, analytical tools to assess impacts on operating cost for transit and fire and rescue providers have been developed. In addition, an analytical tool was developed and employs fuzzy multi-attribute decision making methods to rank alternative transit priority strategies. These analytical tools are proposed for incorporation into the design of a decision support system in the future. / Ph. D.

En sciences économiques, l'une des questions centrales concerne l'allocation des ressources rares et plus particulièrement leur répartition. La décision apparait ainsi au cœur des thématiques économiques, que ce soit en micro-économie ou en macro-économie. Dans un premier temps, nous revenons sur le fait que l’information, élément central de la prise de décision, est imparfaite. En utilisant la théorie des ensembles flous, qui a pour objet de capturer l’imprécision, nous construisons un nombre flou nommé nombre flou C-Shape qui permet de capter la sensibilité du preneur de décision. Nous étudions ensuite la théorie de la décision au travers de deux axes de recherche à savoir (1) la recherche opérationnelle couplée à la théorie des jeux et (2) l’aide à la décision. En premier lieu, Nous faisons une analogie entre la fonction distance et la fonction d’appartenance. Grâce à l’hypothèse de B-convexité et à la fonction C-Shape nous construisons des classes de jeux pour lesquels les joueurs peuvent être optimistes, pessimistes ou neutres, et pour lesquels l’existence d’équilibre de Nash est avérée. Enfin, concernant l’aide à la décision, nous utilisons la fonction C-Shape pour caractériser un nouveau type de critère nommé pseudo critère C-Shape qui permet de considérer les alternatives comme substituables. Ceci permet de prendre en compte, par exemple le contexte institutionnel dans lequel la prise de décision est prise. / Determining the allocation and the distribution of scarce resources is fundamental in economics. Thus, decision theory is the cornerstone of economic theory. In this thesis, we first provide a state of the art insisting on the fact that information, that is a central element of decision-making, is imperfect. Secondly, using fuzzy set theory, which aims to capture imprecision, we construct a fuzzy number, so-called C-Shape that captures the sensitivity of the decision-maker. Thirdly, we study decision theory through two key concepts of operation research: (1) game theory and (2) multi-criteria decision making. We provide an analogy between the gauge functions of convex sets and the membership functions arising in fuzzy set theory. Coupling a suitable notion of -convexity with the C-Shape function, we introduce a class of games for which the players can be optimistic, pessimistic or neutral. In addition the existence of Nash equilibrium is proved for such a class of games. Finally, concerning multi-criteria decision analysis, we use the C-Shape functions to characterize a new type of criteria called C-Shape pseudo-criterion, which makes possible to consider the alternatives as substitutable. This should be of interest to take into account, for example, the institutional context in which decision-making is taken.

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