Mestrado em Informática
URI Permanente para esta coleção
Nível: Mestrado Acadêmico
Ano de início:
Conceito atual na CAPES:
Ato normativo:
Periodicidade de seleção:
Área(s) de concentração:
Url do curso:
Navegar
Submissões Recentes
- ItemHeurística híbrida para o problema de roteamento de veículos com carregamento tridimensional, janelas de tempo e objetivos hierárquicos(Universidade Federal do Espírito Santo, 2025-11-10) Pimentel, Wesley Pereira; Co-orientador1; https://orcid.org/; http://lattes.cnpq.br/; Co-orientador2; https://orcid.org/; http://lattes.cnpq.br/; Co-orientador3; https://orcid.org/; http://lattes.cnpq.br/; Co-orientador4; ID do co-orientador4; Lattes do co-orientador4; Amaral, André Renato Sales ; https://orcid.org/; http://lattes.cnpq.br/; Orientador2; https://orcid.org/; http://lattes.cnpq.br/; https://orcid.org/; http://lattes.cnpq.br/; 1º membro da banca; https://orcid.org/; http://lattes.cnpq.br/; 2º membro da banca; https://orcid.org/; http://lattes.cnpq.br/; 3º membro da banca; https://orcid.org/; http://lattes.cnpq.br/; 4º membro da banca; http://lattes.cnpq.br/; 5º membro da banca; https://orcid.org/; http://lattes.cnpq.br/; 6º membro da banca; https://orcid.org/; http://lattes.cnpq.br/; 7º membro da banca; https://orcid.org/; http://lattes.cnpq.br/This work introduces and formalizes the Three-Dimensional Loading Vehicle Routing Problem with Time Windows and Hierarchical Objectives (3L-VRPTWH). The singularity of the problem lies in its lexicographical objective function, which successively prioritizes the minimization of the number of vehicles, total distance, and waiting time, and in the integration of a robust set of operational constraints. Such constraints include meeting pre-defined time windows, vehicle weight capacity, LIFO (Last In, First Out) unloading policy, and load stability requirements, such as minimum support area and maximum stackable weight. The proposed method consists of a two-stage hybrid heuristic: a pre packing phase with Simulated Annealing to estimate the length space occupied by each customer, followed by an Adaptive Large Neighborhood Search for route optimization. The approach is enhanced by mechanisms such as Adaptive Container Length and the Total Compaction Algorithm, which intensify the search for solutions with more customers per route. Computational experiments, carried out on a set of instances adapted from the literature, confirmed the relevance of the hierarchical formulation, evidencing consistent trade-offs between objectives. The results demonstrate that the method is capable of generating robust and adaptable solutions, reconciling operational efficiency and practical feasibility in complex logistical scenarios. The main contribution of this work is, therefore, the formalization as an optimization problem and the proposal of a solution method, offering a robust tool for logistical scenarios that demand the optimization of multiple criteria with well-defined strategic priorities
- ItemHeurística híbrida para o problema de roteamento de veículos com carregamento tridimensional, janelas de tempo e objetivos hierárquicos(Universidade Federal do Espírito Santo, 2025-11-10) Pimentel, Wesley Pereira; Amaral, André Renato Sales; https://orcid.org/0000-0001-7344-3994; http://lattes.cnpq.br/4695002674556067; https://orcid.org/0000-0002-2847-4078; http://lattes.cnpq.br/9868402229168513; Boeres, Maria Claudia Silva ; https://orcid.org/0000-0001-9801-2410; http://lattes.cnpq.br/0528154281423964; Lorenzoni, Luciano Lessa; https://orcid.org/0000-0003-4859-7750; http://lattes.cnpq.br/7959495705859101This work introduces and formalizes the Three-Dimensional Loading Vehicle Routing Problem with Time Windows and Hierarchical Objectives (3L-VRPTWH). The singularity of the problem lies in its lexicographical objective function, which successively prioritizes the minimization of the number of vehicles, total distance, and waiting time, and in the integration of a robust set of operational constraints. Such constraints include meeting pre-defined time windows, vehicle weight capacity, LIFO (Last In, First Out) unloading policy, and load stability requirements, such as minimum support area and maximum stackable weight. The proposed method consists of a two-stage hybrid heuristic: a pre packing phase with Simulated Annealing to estimate the length space occupied by each customer, followed by an Adaptive Large Neighborhood Search for route optimization. The approach is enhanced by mechanisms such as Adaptive Container Length and the Total Compaction Algorithm, which intensify the search for solutions with more customers per route. Computational experiments, carried out on a set of instances adapted from the literature, confirmed the relevance of the hierarchical formulation, evidencing consistent trade-offs between objectives. The results demonstrate that the method is capable of generating robust and adaptable solutions, reconciling operational efficiency and practical feasibility in complex logistical scenarios. The main contribution of this work is, therefore, the formalization as an optimization problem and the proposal of a solution method, offering a robust tool for logistical scenarios that demand the optimization of multiple criteria with well-defined strategic priorities.
- ItemTRAJES: um arcabouço para geração e avaliação de modelos de predição de trajetórias veiculares(Universidade Federal do Espírito Santo, 2024-12-12) Krohling, Breno Aguiar; Comarela, Giovanni Ventorim; Mota, Vinícius Fernandes Soares; https://orcid.org/0000-0002-8341-8183; Dias, Diego Roberto Colombo; Rettore, Paulo Henrique LopesVehicle trajectories prediction enables traffic management optimization and facilitates solutions that require knowledge of where a vehicle, or its driver, is heading. To use such information on a large scale, it is necessary to employ models capable of generalizing complex movement patterns across an entire region or city. To achieve this, an end-to-end framework called TRAJES (Trajectory Estimator) was proposed to generate models from urban vehicle mobility data, using trajectories consisting only of geolocation information. The model generation and selection are based on concrete metrics, such as the actual distance between predicted and real points, and the proposed Hit Race Accuracy metric, which evaluates model performance based on regions of interest throughout the entire city. The framework was employed to create models capable of predicting vehicle positions in both the near and distant future, tested on real-world datasets collected in the cities of Porto and San Francisco. The results demonstrated the ability to generalize effective models for both prediction scenarios, indicating their viability as an intermediate step for external solutions, particularly those requiring knowledge of a vehicle’s future region.
- ItemAnalysis of bias in GPT language models through fine-tuning with anti-vaccination speech(Universidade Federal do Espírito Santo, 2024-12-02) Turi, Leandro Furlam; Badue, Claudine; Souza, Alberto Ferreira de; https://orcid.org/0000-0003-1561-8447; Pacheco, Andre Georghton Cardoso; Almeida Junior, Jurandy Gomes deWe examined the effects of integrating data containing divergent information, particularly concerning anti-vaccination narratives, in training a GPT-2 language model by fine-tuning it using content from anti-vaccination groups and channels on Telegram. Our objective was to analyze the model’s ability to generate coherent and rationalized texts compared to a model pre-trained on OpenAI’s WebText dataset. The results demonstrate that fine-tuning a GPT-2 model with biased data leads the model to perpetuate these biases in its responses, albeit with a certain degree of rationalization, highlighting the importance of using reliable and high-quality data in the training of natural language processing models and underscoring the implications for information dissemination through these models. We also explored the impact of data poisoning by incorporating anti-vaccination messages combined with general group messages in different proportions, aiming to understand how exposure to biased data can influence text generation and the introduction of harmful biases. The experiments highlight the change in frequency and intensity of anti-vaccination content generated by the model and elucidate the broader implications for reliability and ethics in using language models in sensitive applications. This study provides social scientists with a tool to explore and understand the complexities and challenges associated with misinformation in public health through the use of language models, particularly in the context of vaccine misinformation.
- ItemFrameWeb-LD : uma abordagem baseada em ontologias para a Integração de Sistemas de Informação Web e a Web Semântica(Universidade Federal do Espírito Santo, 2017-11-20) Celino, Danillo Ricardo; Vítor Estêvão Silva Souza; https://orcid.org/0000-0003-1869-5704; http://lattes.cnpq.br/2762374760685577; https://orcid.org/0000-0002-6570-2164; http://lattes.cnpq.br/6786947145681297; Almeida, João Paulo Andrade; https://orcid.org/0000-0002-9819-3781; http://lattes.cnpq.br/4332944687727598; Siqueira, Frank Augusto; https://orcid.org/0000-0002-8275-5751; http://lattes.cnpq.br/6246567808516505With the enormous amount of data available on the Web, Linked Data technologies have been proposed to try and achieve the vision of the Semantic Web, allowing the efficient access, discovery and combination of the available data. Such data should be published in a structured way and bound to known vocabularies, so they can be understood by software agents. Moreover, the abstract conceptual models behind this data, i.e., their ontologies, can also have a great influence in the adoption of a Linked Data set and its vocabularies. In 2007, a Web Engineering method for the design and development of Web applications based on frameworks, named FrameWeb, was proposed, along with an extension of the method, called S-FrameWeb, that proposed the subsequent integration of the applica tion’s data with the Semantic Web. Given the advances of the literature in this area of research, such as well-founded ontologies and the evolution of Linked Data technologies, we propose an evolution of S-FrameWeb called FrameWeb-LD, an approach for the integration of Web-based Information Systems with the Semantic Web. Our proposal uses well-founded languages and methods for the construction of ontologies and aids developers in publishing the application’s data and services in the Web of Data, by offering a system atic process that brings to architectural design models how the data from the system is integrated with Semantic Web vocabularies and a tool that generates automatically most of the source code related to Linked Data publishing