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Metaheuristic strategies for solving scheduling problems for gymnastics competitions

datacite.subject.fosDepartamento de Informáticapt_PT
dc.contributor.advisorFalcão, André Osório e Cruz de Azerêdo, 1969-
dc.contributor.authorNande, Inês Filipa da Silva Furtado
dc.date.accessioned2024-04-15T16:43:52Z
dc.date.available2024-04-15T16:43:52Z
dc.date.issued2024
dc.date.submitted2023
dc.descriptionTese de mestrado, Ciência de Dados, 2023, Universidade de Lisboa, Faculdade de Ciênciaspt_PT
dc.description.abstractThe positioning of teams regarding acrobatic gymnastics can become a challenge considering the complexity of the sport and the restrictions needed for a fair and adequate championship. Competition schedules are organized by blocks that symbolize the interval in the calendar where a predefined set of teams with the same characteristics will act. The starting order defines the positioning of teams in each block. This thesis portrays the research, development, and application of an algorithm that generates an admissible solution for assigning teams in the starting order, explore the hypothesis of generating solutions with hard and soft constraints to provide an admissible solution. Initially, the problem was formalized through theoretical research. Posteriorly, interviews were carried out with judges, athletes, and championship organizers to determine the associated hard and soft constraints. These will define whether or not a starting order is admissible. Due to the type of problem and the complexity of the associated constraints, different types of metaheuristics were tested, specifically local search and evolutionary algorithms. The following methods were selected for implementation: Hill-Climbing (the baseline), Simulated Annealing, and Genetic Algorithm. These models underwent a testing phase in different types of competitions, and computational complexity was also analyzed. Solutions were explored and compared between strategies. Results show that local search methods can modulate different types of schedules in a reasonable amount of time, with the simulated annealing technique providing the best results.pt_PT
dc.identifier.tid203683420
dc.identifier.urihttp://hdl.handle.net/10451/64279
dc.language.isoengpt_PT
dc.subjectOtimizaçãopt_PT
dc.subjectHill Climbingpt_PT
dc.subjectSimulated Annealingpt_PT
dc.subjectAlgoritmo Genéticopt_PT
dc.subjectMetaheurísticaspt_PT
dc.subjectTeses de mestrado - 2024pt_PT
dc.titleMetaheuristic strategies for solving scheduling problems for gymnastics competitionspt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameTese de mestrado em Ciência de Dadospt_PT

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