11 resultados para Hierarchy problem


Relevância:

30.00% 30.00%

Publicador:

Resumo:

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Relevância:

20.00% 20.00%

Publicador:

Resumo:

5th Portuguese Conference on Automatic Control, September, 5-7, 2002, Aveiro, Portugal

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Dissertação apresentada para obtenção do Grau de Doutor em Sistemas de Informação Industriais, Engenharia Electrotécnica, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Dissertação para obtenção do Grau de Mestre em Lógica Computacional

Relevância:

20.00% 20.00%

Publicador:

Resumo:

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

Relevância:

20.00% 20.00%

Publicador:

Resumo:

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Relevância:

20.00% 20.00%

Publicador:

Resumo:

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.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

Nowadays, data available and used by companies is growing very fast creating the need to use and manage this data in the most efficient way. To this end, data is replicated overmultiple datacenters and use different replication protocols, according to their needs, like more availability or stronger consistency level. The costs associated with full data replication can be very high, and most of the times, full replication is not needed since information can be logically partitioned. Another problem, is that by using datacenters to store and process information clients become heavily dependent on them. We propose a partial replication protocol called ParTree, which replicates data to clients, and organizes clients in a hierarchy, using communication between them to propagate information. This solution addresses some of these problems, namely by supporting partial data replication and offline execution mode. Given the complexity of the protocol, the use of formal verification is crucial to ensure the protocol two correctness properties: causal consistency and preservation of data. The use of TLA+ language and tools to formally specificity and verify the proposed protocol are also described.