Determinar curvas a partir de uma série da pontos é uma tarefa importante e muito utilizada em CAD. Este trabalho propõe um algoritmo para determinar uma curva aproximadora representada por diversas curvas de Bézier em sequência a partir de uma sequência de pontos. É utilizada uma abordagem de curvas de Bézier por trechos, onde cada trecho possui continuidade C1-fraca. A otimização é feita pelo recozimento simulado com vizinhança adaptativa que minimiza a soma das distâncias de cada ponto da sequência à curva aproximadora e utiliza o comprimento da curva aproximadora como um fator de regularização. Adicionalmente, é utilizado o recozimento simulado multi-objetivo que avalia a influência da soma das distâncias de cada ponto à curva e do comprimento da curva separadamente. Também é feita uma comparação entre a técnica de ajuste de curvas e a técnica de interpolação de curvas. / The task of determining a curve from a set of points is very important in CAD. This work proposes an algorithm to determine a sequence of Bézier curves that approximate a sequence of points. The piecewise Bézier curve is used, where each curve has C1- weak continuity. The optimization is done using the simulated annealing with adaptive neighborhood aiming at minimizing the sum of the distances from each point of the sequence to the generated curve. The length of this curve is used as a regularization factor. In addition, it is used a multi-objective simulated annealing that evaluates the influence of the sum of the distances from each point to the generated curve, and the curves length. It is also done a comparison between curve fitting and curve interpolation techniques.

Este trabalho trata da proposta de um processo de otimização para o problema do posicionamento rotacional e translacional de formas irregulares em recipientes de dimensões fixas baseado em heurísticas probabilísticas sem o uso de penalização externa. Para tanto, é empregado o polígono de obstrução, acoplado a uma heurística baseada no Recozimento Simulado. O comportamento discreto da função custo em problemas com recipientes de dimensões limitadas foi mitigado através de uma heurística de \"desempate\", que busca diferenciar soluções com valores idênticos através de uma estimativa de quão próxima está uma determinada solução de conseguir encaixar uma forma não-encaixada em seu leiaute. A comparação de resultados deste trabalho com resultados publicados na literatura comprova a validade da abordagem aqui adotada. / This work deals with the proposal of an optimization process for the packing problem with free translations and rotations of irregular shapes on containers with limited dimensions based on probabilistic heuristics without use of extern penalty techniques. For such, the no-fit polygon is used, coupled with an heuristic based on Simulated Annealing. The discrete behavior of the objective function in problems with limited containers is mitigated by a \"tie breaker\" heuristic that sorts solutions with identical values by estimating how close a given solution is of fitting an unplaced shape on its layout. The comparison of these work\'s results with results published on the literature validates the approach here adopted.

Circuitos integrados analógicos são essenciais em sistemas eletrônicos modernos, sendo responsáveis por tarefas como conversão analógica/digital e digital/analógica, comunicação por radiofrequência, filtragem, etc. O projeto deste tipo de circuito e sistema é de grande complexidade uma vez que deve atender a especificações de desempenho cada vez mais exigentes e ter um tempo de projeto reduzido a fim de não comprometer o tempo total dos projetos de sinal misto. Diversas ferramentas são propostas na literatura visando auxiliar o projetista a aumentar sua produtividade. Apesar disso, devido à forte interligação entre etapas, o fluxo de projeto de circuitos integrados analógicos ainda é, tradicionalmente, realizado utilizando-se apenas cálculos manuais e posterior ajuste fino através de softwares de simulação elétrica. Neste trabalho, são estudadas técnicas de síntese de circuitos analógicos utilizando métodos modernos de otimização em nível de circuito e sistema. Após este estudo, é proposto um novo algoritmo de Simulated Annealing/Simulated Quenching, incluindo um mecanismo para utilização do operador de crossover considerando informações de múltiplos objetivos. É realizada a hibridização entre o algoritmo desenvolvido e um algoritmo de Particle Swarm Optimization para criação de um segundo algoritmo capaz de realizar a busca pela fronteira de Pareto. As características dos algoritmos propostos foram elaboradas visando a síntese de circuitos integrados analógicos, no entanto, resultados indicam que eles também têm excelente desempenho em comparação com diversos algoritmos atuais do tipo sem derivada para determinados problemas matemáticos. A generalidade dos métodos modernos de otimização permite que variações da mesma técnica sejam utilizadas em nível de circuito (dimensionamento e polarização de componentes do circuito) e de sistema (tradução de especificações de sistema em especificações de blocos). Dessa forma, são propostas técnicas para a criação de uma ferramenta de síntese em nível de sistema e circuito utilizando métodos modernos de otimização. Uma interface através de arquivos texto de entrada foi desenvolvida para tornar a ferramenta versátil e poder ser utilizada para uma grande variedade de tipos de circuitos eletrônicos. Para validar o algoritmo e a ferramenta na síntese em nível de circuito, foram sintetizados circuitos em tecnologia 0,35 µm, 180 nm e 130 nm. Entre eles, foram sintetizados amplificadores do tipo Miller, amplificadores do tipo folded cascode complementar, amplificadores de baixo ruído operando em 2,45 GHz e fontes de referência. Comparações utilizando o teste não paramétrico de Mann-Whitney-Wilcoxon mostram que o algoritmo proposto tem melhor desempenho que os demais algoritmos comparados para os casos estudados. Comparações com projetos manuais e outras ferramentas confirmam a eficácia dos algoritmos e ferramenta. Para validação da ferramenta em nível de sistema, foram sintetizados filtros do tipo Gm-C. / Analog integrated circuits are very important in modern electronic systems, performing tasks such as analog to digital conversion, digital to analog conversion, radio frequency communication, filtering and others. The design of this type of circuit requires attending to several performance specifications as well as a time specification in order to avoid compromising the overall design time of mixed signal projects. Several tools are proposed in the literature in order to aid the designer, however the traditional design flow for analog integrated circuits is usually accomplished using only hand calculations and adjusts through the use of electrical simulators. In this work, techniques for analog design synthesis for circuit and system level are studied. An optimization algorithm is proposed based on Simulated Annealing/Simulated Quenching with a mechanism for using the crossover operator considering multiobjective information. An hybrid algorithm combining the proposed algorithm with Particle Swarm Optimization was created to properly explore the Pareto front The characteristics of the algorithms are made to enable the synthesis of analog integrated circuits, however, tests indicate they have excellent performance in comparison with many other derivative-free algorithms when applied to certain mathematical problems. The generality of modern optimization methods allow that variations of the same techniques can be used in circuit level (sizing and biasing of circuit components) and in system level (translation of system specifications to block specifications). Therefore, techniques for the creation of a circuit-level and system-level tool are developed. An interface using spice-like text files as inputs is developed to allow the designer to use the tool for a wide range of electronic circuits. In order to validate the proposed algorithms and circuit level tool, circuits were synthesized in 0.35 m, 180 nm and 130 nm. The synthesized circuits included Miller amplifiers, complementary folded cascode amplifiers, low noise amplifiers operating at 2.45 GHz and voltage reference circuits. Comparisons using the non-parametric Mann-Whitney-Wilcoxon test showed that the proposed algorithm has better performance than the compared algorithms for the studied cases. At the system level, syntheses of Gm-C filters were performed to validate the tool.

No description available.

Abstract not available

There are many real world assignment, scheduling and planning tasks which can be classified as combinatorial optimisation problems (COPs). These are usually formulated as a mathematical problem of minimising or maximising some cost function subject to a number of constraints. Usually, such problems are NP hard, and thus, whilst it is possible to find exact solutions to specific problems, in general only approximate solutions can be found. There are many algorithms that have been proposed for finding approximate solutions to COPs, ranging from special purpose heuristics to general search meta-heuristics such as simulated annealing and tabu search. General meta-heuristic algorithms like simulated annealing have been applied to a wide range of problems. In most cases, the designer must choose an appropriate data structure and a set of local operators that define a search neighbourhood. The variability in representation techniques, and suitable neighbourhood transition operators, has meant that it is usually necessary to develop new code for each problem. Toolkits like the one developed by Ingber's Adaptive Simulated Annealing (Ingber 1993, 1996) have been applied to assist rapid prototyping of simulated annealing codes, however, these still require the development of new programs for each type of problem. There have been very few attempts to develop a general meta-heuristic solver, with the notable exception being Connolly's General Purpose Simulated Annealing (Connolly 1992). In this research, a general meta-heuristic based system is presented that is suitable for a wide range of COPs. The main goal of this work is to build an environment in which it is possible to specify a range of COPs using an algebraic formulation, and to produce a tailored solver automatically. This removes the need for the development of specific software, allowing very rapid prototyping. Similar techniques have been available for linear programming based solvers for some years in the form of the GAMS (General Algebraic Modelling System) (Brooke, Kendrick, Meeraus and Raman 1997) and AMPL (Fourer, Gay and Kernighan 1993) interfaces. The new system is based on a novel linked list data structure rather than the more conventional vector notation due to the natural mapping between COPS and lists. In addition, the modelling system is found to be very suitable for processing by meta-heuristic search algorithms as it allows the direct application of common local search operators. A general solver is built that is based on the linked list modelling system. This system is capable of using meta-heuristic search engines such as greedy search, tabu search and simulated annealing. A number of implementation issues such as generating initial solutions, choosing and invoking appropriate local search transition operators and producing suitable incremental cost expressions, are considered. As such, the system can been seen as a good test-bench for model prototypers and those who wish to test various meta-heuristic implementations in a standard way. However, it is not meant as a replacement or substitute for efficient special purpose search algorithms. The solver shows good performance on a wide range of problems, frequently reaching the optimal and best-known solutions. Where this is not the case, solutions within a few percent deviation are produced. Performance is dependent on the chosen transition operators and the frequency with which each is applied. To a lesser extent, the performance of this implementation is influenced by runtime parameters of the meta-heuristic search engine.

<p>Today electronics becomes more and more complex and to keep low costs and power consumption, both digital and analog parts are implemented on the same chip. The degree of automization for the digital parts have increased fast and is high, but for the analog parts this has not come through. This have created a big gap between the degrees of automization for the two parts and makes the analog parts the bottleneck in electronics develop. </p><p>Research is ongoing at Electronics systems group at Linköping University target the increase of design automization for analog circuits. An optimizationbased approach for device sizing is developed and for this a good optimization method is needed which can find good solutions and meet the specification parameters. </p><p>This report contains an evaluation of the optimization method Simulated Annealing. Many test runs have been made to find out good control parameters, both for Adaptiv Simulated Annealing (ASA) and a standard Simulated Annealing method. The result is discussed and all the data is in the enclosures. A popular science and mathematical description is given for Simulated Annealing as well.</p>

<p>In the field of systems biology the task of finding optimal model parameters is a common procedure. The optimization problems encountered are often multi-modal, i.e., with several local optima. In this thesis, a class of algorithms for multi-modal problems called metaheuristics are studied. A downside of metaheuristic algorithms is that they are dependent on algorithm settings in order to yield ideal performance.This thesis studies an approach to tune these algorithm settings using user constructed test functions which are faster to evaluate than an actual biological model. A statistical procedure is constructed in order to distinguish differences in performance between different configurations. Three optimization algorithms are examined closer, namely, scatter search, particle swarm optimization, and simulated annealing. However, the statistical procedure used can be applied to any algorithm that has configurable options.The results are inconclusive in the sense that performance advantages between configurations in the test functions are not necessarily transferred onto real biological models. However, of the algorithms studied a scatter search implementation was the clear top performer in general. The set of test functions used must be studied if any further work is to be made following this thesis.In the field of systems biology the task of finding optimal model parameters is a common procedure. The optimization problems encountered are often multi-modal, i.e., with several local optima. In this thesis, a class of algorithms for multi-modal problems called metaheuristics are studied. A downside of metaheuristic algorithms is that they are dependent on algorithm settings in order to yield ideal performance.</p><p>This thesis studies an approach to tune these algorithm settings using user constructed test functions which are faster to evaluate than an actual biological model. A statistical procedure is constructed in order to distinguish differences in performance between different configurations. Three optimization algorithms are examined closer, namely, scatter search, particle swarm optimization, and simulated annealing. However, the statistical procedure used can be applied to any algorithm that has configurable options.</p><p>The results are inconclusive in the sense that performance advantages between configurations in the test functions are not necessarily transferred onto real biological models. However, of the algorithms studied a scatter search implementation was the clear top performer in general. The set of test functions used must be studied if any further work is to be made following this thesis.</p>

<p>The longitudinal controller at DaimlerChrysler AG consists of two cascade controllers. The outer control loop contains the driver assistance functions such as speed limiter, cruise control, etc. The inner control loop consists of a PID-controller and an observer. The task of the observer is to estimate the part of the vehicle's acceleration caused by large disturbances, for example by a changed vehicle mass or the slope of the road.</p><p>As observer the Kalman filter is selected. It is the optimal filter when the process model is linear and the process noise and measurement noise can be modeled as Gaussian noise. In this Master's thesis the theory for the Kalman filter is presented and it is shown how to choose the filter parameters. Simulated annealing is a global optimization technique which can be used when autotuning, i.e., automatically find the optimal parameter settings. To be able to perform autotuning for the longitudinal controller one has to model the environment and driving situations.</p><p>In this Master's thesis it is verified that the parameter choice is a compromise between a fast but jerky, or a slow but smooth estimate. As the output from the Kalman filter is directly added to the control value for the engine and brakes, it is important that the output is smooth. It is shown that the Kalman filter implemented in the test vehicles today can be exchanged with a first-order lag function, without loss in performance. This makes the filter tuning easier, as there is only one parameter to choose.</p><p>Change detection is a method that can be used to detect large changes in the signal, and react accordingly - for example by making the filter faster. A filter using change detection is implemented and simulations show that it is possible to improve the estimate using this method. It is suggested to implement the change detection algorithm in a test vehicle and evaluate it further.</p>

A hybrid design optimization method combining the stochastic method based on simultaneous perturbation stochastic approximation (SPSA) and the deterministic method of Broydon-Fletcher-Goldfarb-Shanno (BFGS) is developed in order to take advantage of the high efficiency of the gradient based methods and the global search capabilities of SPSA for applications in the optimal aerodynamic shape design of a three dimensional elliptic nozzle. The performance of this hybrid method is compared with that of SPSA, simulated annealing (SA) and gradient based BFGS method. The objective functions which are minimized are estimated by numerically solving the 3D Euler and Navier-Stokes equations using a TVD approach and a LU implicit scheme. Computed results show that the hybrid optimization method proposed in this study shows a promise of high computational efficiency and global search capabilities. / Singapore-MIT Alliance (SMA)