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.

Towards a GIS-T database design and implementation for public transit planning: the case study of Dar-Es-salaam metropolitan city, Tanzania.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Utilização do processador Cell para o processamento de dados obtidos por tomografia aplicada a materiais compósitos

Dissertação de Mestrado em Engenharia Informática

The significance of Traveler's Route Knowledge for Choice of commuting mode of transport

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Desenvolvimento e aplicação do algoritmo enxame de partículas na determinação da máxima injeção nodal em redes de energia elétrica

O objetivo desta dissertação é a determinação da máxima injeção nodal numa rede de energia elétrica, ou seja, qual o valor total máximo de potência ativa que é possível injetar e qual a sua distribuição pelos diversos nós da rede simultaneamente. Determinámos esta máxima injeção nodal em duas situações distintas: injeção não simultânea, injetando potência em um só nó de cada vez e injeção simultânea, injetando potência em todos os nós da rede simultaneamente. Sendo este um problema de natureza combinatória, utilizámos para esta determinação o algoritmo conhecido como nuvem ou enxame de partículas, adaptando-o ao nosso problema. Desenvolvemos o software na linguagem de programação Python utilizando o ambiente Eclipse. Para resolver o trânsito de energia utilizámos o programa PSSE University.Para os exemplos de aplicação utilizámos duas redes de energia elétrica, uma de 6 e outra de 14 barramentos. Estas redes foram baseadas nas redes IEEE 6 BUS e IEEE 14 BUS respetivamente. Concluímos que o algoritmo nuvem ou enxame de partículas cumpriu o objetivo traçado, obtendo as melhores soluções para cada um dos casos, máxima injeção nodal não simultânea e máxima injeção nodal simultânea. No contexto deste problema, o parâmetro chave do algoritmo, comprovado pelos ensaios feitos, é a velocidade máxima de deslocação das partículas, tomando valores típicos de 7 a 10 para a rede de 6 barramentos e de 20 a 25 para a de 14 barramentos.

Pedestrian Priority Zones in the Context of Urban Mobility and Valorization of Public Space

The second half of the XX century was marked by a great increase in the number of people living in cities. Urban agglomerations became poles of attraction for migration flows and these phenomena, coupled with growing car-ownership rates, resulted in the fact that modern transport systems are characterized by large number of users and traffic modes. The necessity to organize these complex systems and to provide space for different traffic modes changed the way cities look. Urban areas had to cope with traffic flows, and as a result nowadays typical street pattern consists of a road for motorized vehicles, a cycle lane (in some cases), pavement for pedestrians, parking and a range of crucial signage to facilitate navigation and make mobility more secure. However, this type of street organization may not be desirable in certain areas, more specifically, in the city centers. Downtown areas have always been places where economic, leisure, social and other types of facilities are concentrated, not surprisingly, they often attract large number of people and this frequently results in traffic jams, air and noise pollution, thus creating unpleasant environment. Besides, excessive traffic signage in central locations can harm the image and perception of a place, this relates in particular to historical centers with architectural heritage.