In this thesis we consider solution approaches for the index tacking problem, in which we aim to reproduces the performance of a market index without purchasing all of the stocks that constitute the index. We solve the problem using three different solution approaches: Mixed Integer Programming (MIP), Genetic Algorithms (GAs), and Ant-colony Optimization (ACO) Algorithm by limiting the number of stocks that can be held. Each index is also assigned with different cardinalities to examine the change to the solution values. All of the solution approaches are tested by considering eight market indices. The smallest data set only consists of 31 stocks whereas the largest data set includes over 2000 stocks. The computational results from the MIP are used as the benchmark to measure the performance of the other solution approaches. The Computational results are presented for different solution approaches and conclusions are given. Finally, we implement post analysis and investigate the best tracking portfolios achieved from the three solution approaches. We summarise the findings of the investigation, and in turn, we further improve some of the algorithms. As the formulations of these problems are mixed-integer linear programs, we use the solver ‘Cplex’ to solve the problems. All of the programming is coded in AMPL.

Na emergente busca por sistemas automáticos que realizem o reconhecimento de faces humanas, pesquisadores têm agrupado diferentes técnicas para obterem resultados que possam ser cada vez mais robustos e ágeis. Essa preocupação não se restringe aos meios acadêmicos, também existe interesse legal comercial em utilizar sistemas que reconheçam faces humanas como por exemplo, que locais em que seja difícil a identificação de pessoas pelos seres humanos. Diante dessa constante preocupação, este trabalho teve como objetivo desenvolver um sistema de reconhecimento automático de faces, por intermédio de suas proporções, aplicando uma técnica inovadora, em que por meio de um algoritmo genético, que tem como entrada o número de segmentos áureos encontrados na face, é possível determinar as proporções existentes e, assim, encontrar a face desejada. Os resultados demonstram que a razão áurea, utilizada desde a antiguidade por pintores e escultores, está presente nas proporções das faces humanas e que fornece um meio de medida biométrica que permite a identificação de um indivíduo, mesmo com expressões faciais. / There has been an emerging pursuit of automatic systems that provide the recognition of human faces. Seeing that, scientists have gathered different techniques in order to obtain more and more positive and concrete results. This pursuit is not of academic concern only, but there is also legal and commercial interest in using systems that can recognize faces in places where it is difficult for humans to locate a person, that is when it is necessary to locate outlaws in crowded places. That being so, this work aims at developing a system for the automatic recognition of human faces using proportions and applying an innovative technique that implements a Genetic Algorithm. This algorithm uses the number of facial golden proportion sections as its input, so it is possible to determine the existing proportions and consequently, to locate the desired face no matter the person\'s facial expression. The results show that the golden ratio, which has been used since the earlier times by painters and sculptors, is present in human facial proportions and is a biometric measurement that enables to identify an individual even when facial expressions are worn.

Na emergente busca por sistemas automáticos que realizem o reconhecimento de faces humanas, pesquisadores têm agrupado diferentes técnicas para obterem resultados que possam ser cada vez mais robustos e ágeis. Essa preocupação não se restringe aos meios acadêmicos, também existe interesse legal comercial em utilizar sistemas que reconheçam faces humanas como por exemplo, que locais em que seja difícil a identificação de pessoas pelos seres humanos. Diante dessa constante preocupação, este trabalho teve como objetivo desenvolver um sistema de reconhecimento automático de faces, por intermédio de suas proporções, aplicando uma técnica inovadora, em que por meio de um algoritmo genético, que tem como entrada o número de segmentos áureos encontrados na face, é possível determinar as proporções existentes e, assim, encontrar a face desejada. Os resultados demonstram que a razão áurea, utilizada desde a antiguidade por pintores e escultores, está presente nas proporções das faces humanas e que fornece um meio de medida biométrica que permite a identificação de um indivíduo, mesmo com expressões faciais. / There has been an emerging pursuit of automatic systems that provide the recognition of human faces. Seeing that, scientists have gathered different techniques in order to obtain more and more positive and concrete results. This pursuit is not of academic concern only, but there is also legal and commercial interest in using systems that can recognize faces in places where it is difficult for humans to locate a person, that is when it is necessary to locate outlaws in crowded places. That being so, this work aims at developing a system for the automatic recognition of human faces using proportions and applying an innovative technique that implements a Genetic Algorithm. This algorithm uses the number of facial golden proportion sections as its input, so it is possible to determine the existing proportions and consequently, to locate the desired face no matter the person\'s facial expression. The results show that the golden ratio, which has been used since the earlier times by painters and sculptors, is present in human facial proportions and is a biometric measurement that enables to identify an individual even when facial expressions are worn.

Ce travail a pour objectif le développement d’une méthodologie de conception de procédés éco-efficaces, avec prise en compte simultanée de considérations écologiques et économiques lors de la phase de conception préliminaire de procédés chimiques. L’aspect environnemental est quantifié à travers l’utilisation d’un ensemble d’indicateurs selon les lignes directrices de concepts de développement durable. Le cadre conceptuel est basé sur une modélisation du procédé et de l’unité de production d’utilités, car l’impact environnemental d’un procédé est lié non seulement aux effluents directs du procédé, mais également à la consommation énergétique, l’effet du recyclage, de la conversion des matières premières … Dans ce but, le logiciel d’aide à la décision ARIANETM dédié à la gestion des utilités des unités de production (vapeur, électricité, eau …) et des effluents (CO2, SO2, NOx, etc..) a été couplé au modèle d’un procédé pour déterminer les besoins en énergies primaires et quantifier les émissions polluantes. Ces modèles ont ensuite été intégrés au sein d’une boucle d’optimisation multiobjectif, basée sur une variante d’un algorithme génétique multiobjectif de type NSGA-II (Non Sorted Genetic Algorithm). Le compromis entre les objectifs économiques et écologiques est illustré à travers la génération de fronts de Pareto. La sélection des meilleures solutions parmi cet ensemble est effectuée par utilisation de techniques d’analyse multicritère. L’exemple test bien connu du procédé de production de benzène par hydrodésalkylation du toluène (HDA) est revisité ici dans un mode multiobjectif pour illustrer l’utilité de l’approche pour trouver des solutions de conception économiques et écologiques. / This study aims at the development of a design methodology for eco-efficient processes, meaning that ecological and economic considerations are taken into account simultaneously at the preliminary design phase of chemical processes. The environmental aspect is quantified by using of a set of indicators following the guidelines of sustainability concepts. The design framework is based on a modelling approach considering both process and utility production units, since the environmental impact of a chemical process not only contains the material involved in the process but also the energy consumption, the effect of flow recycle, material conversion and so on... For this purpose, a decision support tool dedicated to the management of plant utilities (steam, electricity, water...) and pollutants (CO2, SO2, NOx, etc..), (ARIANETM package) was coupled to process modelling and used here both to compute the primary energy requirements of the process and to quantify its pollutant emissions. Both models were thus integrated in an outer multiobjective optimization loop, based on a variant of the so-called NSGA-II (Non Sorted Genetic Algorithm) multiobjective genetic algorithm. The trade-off between economic and environmental objectives is illustrated through the generation of Pareto fronts. The selection of the best design alternatives is performed through the use of multicriteria analysis. The well-known benchmark process for hydrodealkylation (HDA) of toluene to produce benzene, revisited here in a multi-objective mode, is used to illustrate the usefulness of the approach in finding environmentally friendly and cost-effective designs.