2020-03-102020-03-102019-07-1031st International Conference on Software Engineering & Knowledge Engineering (2019)http://hdl.handle.net/20.500.12272/4397In search-based software engineering (SBSE), software engineers usually have to select one among many quasi-optimal solutions with different values for the objectives of interest for a particular problem domain. Because of this, a metaheuristic algorithm is needed to explore a larger extension of the Pareto optimal front to provide a bigger set of possible solutions. In this regard the Fuzzy Multi-Objective Particle Swarm Optimization (FMOPSO), a novel a posteriori algorithm, is proposed in this paper and compared with other state-of-the-art algorithms. The results show that FMOPSO is adequate for finding very detailed Pareto Fronts.application/pdfenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/Software engineeringMulti-objective optimizationParticle swarm optimizationNext release problemFuzzy logicinfo:eu-repo/semantics/conferenceObjectCasanova Pietroboni, Carlos Antonio ; Rottoli, Giovanni Daián ; Schab, Esteban Alejandro ; Bracco, Luciano Joaquín ; Pereyra Rausch, Fernando Nahuel ; De Battista, Anabella CeciliaNo comercial con fines académicos.Attribution-NonCommercial-NoDerivatives 4.0 Internacional10.18293/SEKE2019-082