Bullwhip effect, in production control: a comparison between traditional methods and LPS

21th Annual Conference of the International Group for Lean Construction (IGLC 21), July 2013, Fortaleza, Brazil

Service-oriented infrastructure to support the control, monitoring and management of a shop floor system

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Numerical methods and tangible interfaces for pollutant dispersion simulation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia do Ambiente, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Introduction: digital methods and tools for historical research

As an introduction to a series of articles focused on the exploration of particular tools and/or methods to bring together digital technology and historical research, the aim of this paper is mainly to highlight and discuss in what measure those methodological approaches can contribute to improve analytical and interpretative capabilities available to historians. In a moment when the digital world present us with an ever-increasing variety of tools to perform extraction, analysis and visualization of large amounts of text, we thought it would be relevant to bring the digital closer to the vast historical academic community. More than repeating an idea of digital revolution introduced in the historical research, something recurring in the literature since the 1980s, the aim was to show the validity and usefulness of using digital tools and methods, as another set of highly relevant tools that the historians should consider. For this several case studies were used, combining the exploration of specific themes of historical knowledge and the development or discussion of digital methodologies, in order to highlight some changes and challenges that, in our opinion, are already affecting the historians' work, such as a greater focus given to interdisciplinarity and collaborative work, and a need for the form of communication of historical knowledge to become more interactive.

Electrodialytic remediation of two types of air pollution control residues and their applicability in construction materials

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente Perfil de Engenharia de Sistemas Ambientais

How different generations contact and search for brands on social media? Comparing gen X and Y

This research intends to examine if there were significant differences on the brand engagement and on the electronic word of mouth (e-WOM)1 referral intention through Facebook between Generation X and Generation Y (also called millennials). Also, this study intends to examine if there are differences in the motivations that drive these generations to interact with brands through Facebook. Results indicated that Generation Y members consumed more content on Facebook brands’ pages than Generation X. Also, they were more likely to have an e-WOM referral intention as well as being more driven by brand affiliation and opportunity seeking. Finally, currently employed individuals were found to contribute with more content than students. This study fills the gap in the literature by addressing how marketing professionals should market their brand and interact and engage with their customers, based on customers’ generational cohort.

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.