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During evacuations, emergency managers and departments of transportation seek to facilitate the movement of citizens out of impacted or threatened areas. One strategy they may consider is crossing elimination, which prohibits certain movements at intersections, that may be permissible under normal operating conditions. A few previous studies examined this strategy in conjunction with contra-flow operations, but fewer have considered crossing elimination by itself. This study helps fill the existing gap in knowledge of the individual effects of crossing elimination. A bi-level model that iterates between optimization and simulation is developed to determine the optimal configuration of intersection movements from a set of pre-specified possible configurations for intersections in a given area. At the upper level, evacuees' travel time is minimized and at the lower level, traffic is assigned to the network with the traffic assignment-simulation software DynusT. The overall model is solved with a simulated annealing heuristic and applied to a real case study to assess the impact of crossing elimination. Three scenarios are developed and examined using the solution method proposed in this research. These scenarios are developed using combinations of two elements: (1) Evacuee destination distributions, and (2) Evacuee departure time distributions. Results showed about 3-5 percent improvement in total evacuee travel time can be achieved in these scenarios. Availability of through movements at intersections and existing merging points in movement configurations are the two factors influencing the selection of movement configurations. / Master of Science

This thesis focuses on an adaptive quadratic spiking model of a motoneuron that is both versatile in its ability to represent a range of experimentally observed neuronal firing patterns as well as computationally efficient for large network simulation. The objective of research is to fit membrane voltage data to the model using a parameter estimation approach involving simulated annealing. By manipulating the system dynamics of the model, a realizable model with linear parameterization (LP) can be obtained to simplify the estimation process. With a persistently excited current input applied to the model, simulated annealing is used to efficiently determine the best model parameters that minimize the square error function between the membrane voltage reference data and data generated by the LP model. Results obtained through simulation of this approach show feasibility to predict a range of different neuron firing patterns.

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No / The effective maintenance scheduling of power system generators is very important for the economical and reliable operation of a power system. This represents a tough scheduling problem which continues to present a challenge for efficient optimization solution techniques. This paper presents the application of metaheuristic approaches, such as a genetic algorithm (GA), simulated annealing (SA) and their hybrid for generator maintenance scheduling (GMS) in power systems using an integer representation. This paper mainly focuses on the application of GA/SA and GA/SA/heuristic hybrid approaches. GA/SA hybrid uses the probabilistic acceptance criterion of SA within the GA framework. GA/SA/heuristic hybrid combines heuristic approaches within the GA/SA hybrid to seed the initial population. A case study is formulated in this paper as an integer programming problem using a reliability-based objective function and typical problem constraints. The implementation and performance of the metaheuristic approaches and their hybrid for the test case study are discussed. The results obtained are promising and show that the hybrid approaches are less sensitive to the variations of technique parameters and offer an effective alternative for solving the generator maintenance scheduling problem.

This thesis presents the use of sliding mode control applied to a 1/10th scale robotic car to operate at a desired slip. Controlling the robot car at any desired slip has a direct relation to the amount of force that is applied to the driving wheels based on road surface conditions. For this model, the desired traction/slip is maintained for a specific surface which happens to be a Lego treadmill platform. How the platform evolved and the robot car was designed are also covered. To parameterize the system dynamics, simulated annealing is used to find the minimal error between mathematical simulations and physical test results. Also discussed is how the robot car and microprocessor can be modeled as a hybrid system. The results from testing the robot car at various desired percent slip show that it is possible to control the slip dynamics of a 1/10th scale automated robotic car and thus pave the way for further studies using scaled model cars to test an automated highway system. / Master of Science

Com os rápidos avanços no seqüenciamento do genoma, a compreensão da estrutura de proteínas torna-se uma extensão crucial a esses progressos. Apesar dos significativos avanços tecnológicos recentes, a determinação experimental da estrutura terciária de proteínas ainda é muito lenta se comparada com a taxa de acúmulo de dados das seqüências de aminoácidos. Isto torna o enovelamento de proteínas um problema central para o desenvolvimento da biologia pós-genômica. Em nosso trabalho, fazemos uso de um método de otimização, o Generalized Simulated Annealing (GSA), baseado na termoestatística generalizada por Tsallis. Embora o GSA seja um procedimento geral, sua eficiência depende não apenas da escolha apropriada de parâmetros, mas também das características topológicas da hiper--superfície de energia da função custo. Com o mapeamento dos parâmetros necessários à aplicação do GSA, pode-se reduzir significativamente o número de escolhas, além de tornar possível uma análise do efeito dos parâmetros no comportamento do algoritmo. Como passo inicial, usamos estruturas conhecidas, com as quais os resultados obtidos com o GSA possam ser comparados, como é o caso das polialaninas. Além disso, aplicamos, o GSA a três peptídeos de proteínas ribossomais da família P, de considerável importância no estudo da doença de Chagas. Cada um possui 13 aminoácidos, diferindo em apenas uma mutação não conservativa no terceiro aminoácido. Como os peptídeos não possuem estrutura experimentalmente resolvida, analisamos os resultados obtidos com GSA seguidos por simulações de Dinâmica Molecular. A validade destes resultados é estudada, de forma que, no futuro, estruturas desconhecidas possam ser determinadas com certo grau de confiabilidade. / As the genome sequencing advances, the comprehension of protein structures becomes a crucial extension to these progresses. In spite of the numerous recent technological advances, experimental determination of protein terciary structures is still very slow compared to the accumulated data from amino acid sequences. That is what makes the protein folding a central problem to the development of the pots-genomic era. In this work we use an optimization method, the Generalized Simulated Annealing (GSA), which is based on Tsallis' generalized thermostatistics, to investigate the protein folding problem. Although GSA is a generic procedure, its efficiency depends not only on the appropriate choice of parameters, but also on topological characteristics of the energy hypersurface. By mapping all the GSA parameters, it can be possible to reduce the number of possible choices of them. That also allows an analysis of its effects on the algorithm behavior. As a initial step, we apply GSA to known structures, such as polyalanines. In sequence, we also apply GSA to three more peptides of ribosomal P proteins, which are of considerable importance on the comprehension of Chagas' heart disease. Each one contains 13 amino acids and differ only on the third residue by a non-conservative mutation. As these peptides do not have experimentally resolved structure, we analyze results obtained from GSA followed by Molecular Dynamics simulations. Validity of these results is studied such that, in the future, unknown structures can be determined by this technique with a higher degree of confidence.

Orientadores: Reginaldo Guirardello, Lucio Cardozo-Filho / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-09T05:19:46Z (GMT). No. of bitstreams: 1 Jesus_LorenaBrancagliaode_M.pdf: 1007051 bytes, checksum: 2881509687072c829010312b1b5653e0 (MD5) Previous issue date: 2007 / Resumo: O conhecimento do equilíbrio de fases é de grande importância no projeto e análise de uma grande variedade de processos químicos, incluindo reatores e unidades de separação. É o caso, por exemplo, da indústria de produção de óleos vegetais e de produção de ácido cítrico. Geralmente, sistemas de interesse da indústria alimentícia são formados por muitos componentes. A determinação e o cálculo das propriedades termodinâmicas e do equilíbrio de fases, nesses casos, são bastante complicados. Devido à natureza não-convexa e não-linear de modelos termodinâmicos, necessários para descrever o problema do equilíbrio de fases, há um grande interesse na aplicação de técnicas de otimização para descrever o comportamento do equilíbrio. Problemas de otimização global, técnicas rápidas, seguras e robustas que têm certo grau de confiança para achar a solução global não foram ainda completamente desenvolvidos. Por isso, estudos desses métodos têm sido foco na simulação e otimização na engenharia química. Este trabalho tem como objetivo o estudo e aplicação de um método de busca estocástica para otimização global no cálculo do equilíbrio de fases de misturas complexas de sistemas de interesse da industria alimentícia. O método de busca estocástica utilizado é o algoritmo ¿simulated annealing¿ (SA) devido à sua principal vantagem em poder evitar mínimos locais (teoricamente) e de ser de fácil aplicação. A determinação do equilíbrio de fases é feita pela minimização da energia livre de Gibbs do sistema. Para a representação termodinâmica de misturas complexas de interesse da indústria alimentícia foram empregados os modelos NRTL (Non-Random-Two-Liquid) e UNIQUAC (UNIversal QUAsi-Chemical). Os dados experimentais utilizados como estudo de caso foram obtidos na literatura e foram caracterizados por meio de pseudo-componentes, uma vez que são formados por muitas substâncias diferentes. Os resultados obtidos para os casos estudados demonstraram que a aplicação da técnica de SA para minimização global da energia livre de Gibbs permite, juntamente com os modelos NRTL e UNIQUAC, a representação confiável dos dados experimentais em tempos muito bons de execução. Além disso, a técnica de SA mostrou-se robusta levando a resultados de mínimo global independentemente da estimativa inicial, mesmo para casos fortemente não-lineares e não-convexos / Abstract: In many industrial processes, during the phase of refining and separation, products form very complex mixtures. It is the case, for example, of the vegetal oil and citric acid industries. As these mixtures are formed by many components, determination and calculation of thermodynamic properties and phase equilibrium are very complicated. In this way, the use of the most rigorous methods able to calculate the phase equilibrium and to analyse the stability of phases of these mixtures becomes necessary. In this work, the determination of phase equilibrium is done by minimization of the Gibbs free energy of the system. The NRTL (Non-Random-Two-Liquid) and UNIQUAC (UNIversal QUAsi-Chemical) models were used for the thermodynamic representation of the complex mixtures, which were characterized by means of pseudo-components. Under conditions of constant temperature and pressure, the necessary and sufficient condition for a multiphase and multicomponent system to reach the equilibrium is that the Gibbs free energy is a global minimum. Based on this principle, equilibrium problems can be formulated and solved as otimization problems. The objective function for these problems is generaly highly nonlinear and usually nonconvex, and methods of global optimization are generally necessary for its minimization. The technique of global optimization studied and applied in this work is a method of random search named Simulated Annealing (SA), whose main advantages are the ability to avoid local minimum and the ease of application. The results obtained for the studied cases have demonstrated that the application of the technique of SA for global minimization of the Gibbs free energy, together with the models NRTL and UNIQUAC, allows a reliable representation of the experimental data in very short execution times. Moreover, the SA technique was robust, leading to the global minima independently of the initial estimate even for highly nonlinear and nonconvex cases / Mestrado / Desenvolvimento de Processos Químicos / Mestre em Engenharia Química