A genetic algorithm for the resource constrained multi-project scheduling problem

This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.

A genetic algorithm for project scheduling with multi-modes and renewable resources

This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.

Project scheduling under multiple resources constraints using a genetic algorithm

The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Project scheduling using a competitive genetic algorithm

- The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm

A biased random-key genetic algorithm with forward-backward improvement for the resource constrained project scheduling problem

This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

A two-level genetic algorithm for the multi-mode resource-constrained project scheduling problem

This paper presents a genetic algorithm for the multimode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. The objective function is the minimization of the construction project completion time. To solve the problem, is applied a two-level genetic algorithm, which makes use of two separate levels and extend the parameterized schedule generation scheme by introducing an improvement procedure. It is evaluated the quality of the schedule and present detailed comparative computational results for the MRCPSP, which reveal that this approach is a competitive algorithm.

TRAILER project overview: tagging, recognition and acknowledgment of informal learning experiences

The evolution of new technology and its increasing use, have for some years been making the existence of informal learning more and more transparent, especially among young and older adults in both Higher Education and workplace contexts. However, the nature of formal and non-formal, course-based, approaches to learning has made it hard to accommodate these informal processes satisfactorily, and although technology bring us near to the solution, it has not yet achieved. TRAILER project aims to address this problem by developing a tool for the management of competences and skills acquired through informal learning experiences, both from the perspective of the user and the institution or company. This paper describes the research and development main lines of this project.

Plano de Emergência Interno do Instituto Superior de Engenharia do Porto

Mestrado em Engenharia Civil – Ramo Tecnologias da Construção

Sistema de Torre de Refrigeração

Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química

Determinação do teor de compostos aromáticos policíclicos de óleos minerais isolantes para transformadores

Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química

A random key based genetic algorithm for the resource constrained project scheduling problem

This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm. The heuristic generates parameterized active schedules. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Desenvolvimento de recursos educativos em dispositivos móveis - RealHiBook

Nos últimos anos têm existido bastantes pesquisas e um grande investimento quer na área da educação à distância quer ao nível das tecnologias móveis. A dada altura percebeu-se que cada vez mais poderiam ser utilizados dispositivos móveis no contexto da educação e de que estes já seriam capazes de responder às exigências necessárias para que fosse possível criar ou melhorar cenários com recursos educativos. Este trabalho tem como objetivo propor um modelo que facilite a aprendizagem em dispositivos móveis. Nesse sentido, decidiu-se que seria uma mais-valia adicionar a este projeto, a utilização da Realidade Aumentada como potenciador de melhorias no processo de aprendizagem. A Realidade Aumentada, a par do que acontece com a educação à distância e com as tecnologias móveis, é uma área alvo de constantes investigações e inovação. Apresenta como principal capacidade a interação do utilizador com vários modelos virtuais incluídos numa cena real. Esta capacidade proporciona experiências que podem contribuir para o aumento da motivação e da perceção por parte dos alunos. A forma como o utilizador interage com as aplicações móveis é vista com extrema importância, principalmente na área da educação. Aliar uma boa interação à utilização da Realidade Aumentada, é parte integrante deste trabalho. Foram estudados exemplos de interações e formas como o utilizador vive a experiência durante a utilização de aplicações que partilham o mesmo tipo de tecnologias utilizadas neste projeto. O objetivo final foca-se na criação de uma aplicação, capaz de fornecer uma experiência enriquecedora no âmbito do ensino, ligado ao tema história e que consiga fundamentar a criação de um modelo que facilite a aprendizagem utilizando plataformas móveis. Os objetivos são corroborados por um conjunto de testes efetuados à aplicação e pelos resultados obtidos através de um questionário feito a um grupo de pessoas que testaram o protótipo.

Desenvolvimento de Ontologia para Apoio ao Diagnóstico de Distúrbios do Humor

Mestrado em Computação e Instrumentação Médica

Project, modelling and simulation of air stripping columns for the treatment of groundwater contaminated with volatile organic compounds

Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for the column design for any particular type of packing and contaminant avoiding the necessity of a pre-defined diameter used in the classical approach. It also renders unnecessary the employment of the graphical Eckert generalized correlation for pressure drop estimates. The hydraulic features are previously chosen as a project criterion and only afterwards the mass transfer phenomena are incorporated, in opposition to conventional approach. The design procedure was translated into a convenient algorithm using C++ as programming language. A column was built in order to test the models used either in the design or in the simulation of the column performance. The experiments were fulfilled using a solution of chloroform in distilled water. Another model was built to simulate the operational performance of the column, both in steady state and in transient conditions. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting system of ODE can be solved, allowing for the calculation of the concentration profile in both phases inside the column. In transient state the system of PDE was numerically solved by finite differences, after a previous linearization.

Acqusition and data analysis of the eco-efficiency for the establishment of indicators parameters for industrial environmental sustainability

The industrial activity is inevitably associated with a certain degradation of the environmental quality, because is not possible to guarantee that a manufacturing process can be totally innocuous. The eco-efficiency concept is globally accepted as a philosophy of entreprise management, that encourages the companies to become more competitive, innovative and environmentally responsible by promoting the link between its companies objectives for excellence and its objectives of environmental excellence issues. This link imposes the creation of an organizational methodology where the performance of the company is concordant with the sustainable development. The main propose of this project is to apply the concept of eco-efficiency to the particular case of the metallurgical and metal workshop industries through the development of the particular indicators needed and to produce a manual of procedures for implementation of the accurate solution.