Loading...
115 results
Search Results
Now showing 1 - 10 of 115
- Introdução à programação: memóriaPublication . Coelho, JoséIntroduz-se os 4 capítulos do módulo 3. Revelam-se algumas limitações dos programas no módulo anterior. Explica-se o stack (variáveis locais) na programação, o que é e porque é essencial. Este foi o método de alocação de memória do módulo anterior. Introduz-se a alternativa com a memória dinâmica (heap) na programação, o que é e porque é essencial. Mostra-se como utilizar o heap na linguagem C, e listam-se os erros mais comuns na utilização do heap. Termina-se com alguns erros de qualidade de código.
- A genetic algorithm for the resource-constrained project scheduling problem with alternative subgraphs using a boolean satisfiability solverPublication . Servranckx, Tom; Coelho, José; Vanhoucke, MarioThis study evaluates a new solution approach for the Resource-Constrained Project Scheduling with Alternative Subgraphs (RCPSP-AS) in case that complex relations (i.e. nested and linked alternatives) are considered. In the RCPSP-AS, the project activity structure is extended with alternative activity sequences. This implies that only a subset of all activities should be scheduled, which corresponds with a set of activities in the project network that model an alternative execution mode for a work package. Since only the selected activities should be scheduled, the RCPSP-AS comes down to a traditional RCPSP problem when the selection subproblem is solved. It is known that the RCPSP and, hence, its extension to the RCPSP-AS is NP-hard. Since similar scheduling and selection subproblems have already been successfully solved by satisfiability (SAT) solvers in the existing literature, we aim to test the performance of a GA-SAT approach that is derived from the literature and adjusted to be able to deal with the problem-specific constraints of the RCPSP-AS. Computational results on small and large-scale instances (both artificial and empirical) show that the algorithm can compete with existing metaheuristic algorithms from the literature. Also, the performance is compared with an exact mathematical solver and learning behaviour is observed and analysed. This research again validates the broad applicability of SAT solvers as well as the need to search for better and more suited algorithms for the RCPSP-AS and its extensions.
- A prediction model for ranking branch-and-bound procedures for the resource-constrained project scheduling problemPublication . Guo, Weikang; Vanhoucke, Mario; Coelho, JoséThe branch-and-bound (B&B) procedure is one of the most widely used techniques to get optimal solutions for the resource-constrained project scheduling problem (RCPSP). Recently, various components from the literature have been assembled by Coelho and Vanhoucke (2018) into a unified search algorithm using the best performing lower bounds, branching schemes, search strategies, and dominance rules. However, due to the high computational time, this procedure is only suitable to solve small to medium-sized problems. Moreover, despite its relatively good performance, not much is known about which components perform best, and how these components should be combined into a procedure to maximize chances to solve the problem. This paper introduces a structured prediction approach to rank various combinations of components (configurations) of the integrated B&B procedure. More specifically, two regression methods are used to map project indicators to a full ranking of configurations. The objective is to provide preference information about the quality of different configurations to obtain the best possible solution. Using such models, the ranking of all configurations can be predicted, and these predictions are then used to get the best possible solution for a new project with known network and resource values. A computational experiment is conducted to verify the performance of this novel approach. Furthermore, the models are tested for 48 different configurations, and their robustness is investigated on datasets with different numbers of activities. The results show that the two models are very competitive, and both can generate significantly better results than any single-best configuration.
- Raciocínio e Representação do Conhecimento: 3 - InferênciaPublication . Carvalho, Gracinda; Coelho, JoséApresentamos os métodos de inferência em lógica de primeira ordem. Iniciamos com a relação entre lógica proposicional e lógica de 1ª ordem, introduzimos a regra do Modus Ponens generalizado, e o unificador mais geral. Abordamos as provas com Modus Ponens generalizado e com resolução.
- Arquitetura de Computadores. Capítulo 7 - Análise e projeto de circuitos sequenciaisPublication . Coelho, José; Carvalho, GracindaCircuitos sequenciais síncronos são aqueles que dependem de um sinal de relógio para atualizar seus estados internos. Eles podem ser usados para modelar sistemas que reagem a eventos externos e internos, como máquinas de estado finito. Vamos ver como especificar informalmente e formalmente esses circuitos usando diagramas de estados e fluxogramas. Diagramas de estados mostram os possíveis estados do circuito e as transições entre eles, enquanto fluxogramas mostram o fluxo lógico das operações realizadas pelo circuito.
- Raciocínio e Representação do Conhecimento: Apresentação da Unidade CurricularPublication . Carvalho, Gracinda; Coelho, JoséApresentamos a unidade curricular de Raciocínio e Representação do Conhecimento da Universidade Aberta. A unidade curricular centra-se nos aspetos da Inteligência Artificial relacionados com a representação do conhecimento, raciocínio com incerteza e aprendizagem. Mostramos uma visão geral da matéria, metodologia, avaliação e recursos disponíveis.
- Introdução à Inteligência Artificial: conceito de agentePublication . Coelho, JoséApresentamos o conceito de Agente de Inteligência Artificial. Abordaremos o conceito de agente, as suas características e propriedades do ambiente em que atua, bem como os tipos de agentes que existem.
- New resource-constrained project scheduling instances for testing (meta-)heuristic scheduling algorithmsPublication . Coelho, José; Vanhoucke, MarioThe resource-constrained project scheduling problem (RCPSP) is a well-known scheduling problem that has attracted attention since several decades. Despite the rapid progress of exact and (meta-)heuristic procedures, the problem can still not be solved to optimality for many problem instances of relatively small size. Due to the known complexity, many researchers have proposed fast and efficient meta-heuristic solution procedures that can solve the problem to near optimality. Despite the excellent results obtained in the last decades, little is known why some heuristics perform better than others. However, if researchers better understood why some meta-heuristic procedures generate good solutions for some project instances while still falling short for others, this could lead to insights to improve these meta-heuristics, ultimately leading to stronger algorithms and better overall solution quality. In this study, a new hardness indicator is proposed to measure the difficulty of providing near-optimal solutions for meta-heuristic procedures. The new indicator is based on a new concept that uses the 𝜎 distance metric to describe the solution space of the problem instance, and relies on current knowledge for lower and upper bound calculations for problem instances from five known datasets in the literature. This new indicator, which will be called the 𝜎𝐷 indicator, will be used not only to measure the hardness of existing project datasets, but also to generate a new benchmark dataset that can be used for future research purposes. The new dataset contains project instances with different values for the 𝜎𝐷 indicator, and it will be shown that the value of the 𝜎 distance metric actually describes the difficulty of the project instances through two fast and efficient meta-heuristic procedures from the literature.
- Descoberta de padrões sequenciais utilizando árvores orientadasPublication . Cavique, Luís; Coelho, JoséHoje em dia, a descoberta de padrões sequenciais em grandes bases de dados é um assunto de grande interesse. A maior parte dos algoritmos de padrões sequenciais usam estruturas de memória muito grandes no espaço de soluções e geram um número enorme de regras. Com a utilização do modelo das cadeias de Markov é possível ter uma visão global, já que todos os itens são tomados em consideração. Contudo, para grandes matrizes nas cadeias de Markov, a complexidade do problema cresce muito rapidamente. Neste artigo pretendemos manter a visão global dos itens e evitar tempos computacionais não-polinomiais. Usando heurísticas baseadas no algoritmo de Prim, árvores e poli-árvores podem ser encontradas em redes cíclicas. Os resultados computacionais são apresentados para grandes bases de dados, criadas com um conhecido gerador artificial de dados de teste.
- Exames online em segurançaPublication . Coelho, JoséApresentação efetuada nas IV Jornadas de Informática da Universidade Aberta