FRCU - GIICIS: Grupo de Investigación en Inteligencia Computacional e Ingeniería de Software - Artículos
Permanent URI for this collectionhttp://48.217.138.120/handle/20.500.12272/4095
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Item Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem(Hector Florez, Universidad Distrital Francisco Jose de Caldas, Colombia., 2023-05-24) Casanova Pietroboni, Carlos Antonio; Schab, Esteban Alejandro; Prado, Lucas Martín; Rottoli, Giovani DaianWhen solving multi-objective combinatorial optimization problems using a search algorithm without a priori information, the result is a Pareto front. Selecting a solution from it is a laborious task if the number of solutions to be analyzed is large. This task would benefit from a systematic approach that facilitates the analysis, comparison and selection of a solution or a group of solutions based on the preferences of the decision makers. In the last decade, the research and development of algorithms for solving multi-objective combinatorial optimization problems has been growing steadily. In contrast, efforts in the a posteriori exploration of non-dominated solutions are still scarce.