Combining non-dominance, objective-order and spread metric to extend firefly algorithm to multi-objective optimization

In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

Development of a methodology to incorporate risk and uncertainty in electricity power planning

Dissertação de mestrado em Engenharia Industrial

Estudo e implementação de modelos de gestão de stocks em sistemas ERP para empresas retalhistas

Dissertação de mestrado em Engenharia de Sistemas

Numerical simulation of the reflow soldering process

Dissertação de mestrado integrado em Mechanical Engineering

Estudo, projeto e desenvolvimento de uma máquina para montar e vincar sacos de papel

Dissertação de mestrado integrado em Engenharia Mecânica

An interactive web-based tool for breast reduction surgery simulation

In this work, we present a 3D web-based interactive tool for numerical modeling and simulation approach to breast reduction surgery simulation, to assist surgeons in planning all aspects related to breast reduction surgery before the actual procedure takes place, thereby avoiding unnecessary risks. In particular, it allows the modeling of the initial breast geometry, the definition of all aspects related to the surgery and the visualization of the post-surgery breast shape in a realistic environment.

Caracterização e otimização de uma vitrine frigorífica

Dissertação de mestrado integrado em Engenharia Mecânica

Simulação numérica do comportamento ao impacto de componentes metálicos para aplicações de crashworthiness utilizando iniciadores de deformação configuráveis

Dissertação de mestrado integrado em Engenharia Mecânica

Análise e simulação da produção de moldes para injeção de plásticos

Dissertação de mestrado em Engenharia Industrial

Optimization of magnetoelectric composites based on electroactive polymers for energy harvesting and sensor application

Tese de Doutoramento em Engenharia de Materiais.

Protein-based nanodevices for therapeutic applications

Tese de Doutoramento em Biologia Molecular e Ambiental (área de especialização em Biologia Celular e Saúde).

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

Implementação de um sistema de previsão e controlo para operação otimizada de um sistema de recolha e armazenamento de água pluvial

Dissertação de mestrado integrado em Engenharia Civil

Optimization of low-cost nutritional supplementation for lignocellulosic ethanol fermentation

[Excerpt] Bioethanol from lignocellulosic materials (LCM), also called second generation bioethanol, is considered a promising alternative to first generation bioethanol. An efficient production process of lignocellulosic bioethanol involves an effective pretreatment of LCM to improve the accessibility of cellulose and thus enhance the enzymatic saccharification. One interesting approach is to use the whole slurry from treatment, since allows economical and industrial benefits: washing steps are avoided, water consumption is lower and the sugars from liquid phase can be used, increasing ethanol concentration [1]. However, during the pretreatment step some compounds (such as furans, phenolic compounds and weak acids) are produced. These compounds have an inhibitory effect on the microorganisms used for hydrolysate fermentation [2]. To overcome this, the use of a robust industrial strain together with agro-industrial by-products as nutritional supplementation was proposed to increase the ethanol productivities and yields. (...)