Guerrero Madrid, José LuisBerlanga de Jesús, AntonioMolina López, José Manuel2015-10-082015-10-082013Omatu, S., et al. (eds.) Distributed Computing and Artificial Intelligence: 10th International Conference. (pp. 171-178). (Advances in Intelligent Systems and Computing; 217). Springer International Publishing.978-3-319-00550-8 (print)978-3-319-00551-5 (online)2194-5357https://hdl.handle.net/10016/21676Proceedings of: 10th International Symposium on Distributed Computing and Artificial Intelligence . University of Salamanca (DCAI 2013). Salamanca, Spain, Spain, May 22-24, 2013.Polygonal approximation is based on the division of a closed curve into a set of segments. This problem has been traditionally approached as a single-objective optimization issue where the representation error was minimized according to a set of restrictions and parameters. When these approaches try to be subsumed into more recent multi-objective ones, a number of issues arise. Current work successfully adapts two of these traditional approaches and introduces them as initialization procedures for a MOEA approach to polygonal approximation, being the results, both for initial and final fronts, analyzed according to their statistical significance over a set of traditional curves from the domain.8application/pdfeng© 2013 Springer International Publishing SwitzerlandPolygonal approximationMulti-Objective Evolutionary AlgorithmsPareto-optimal frontEvolutionary algorithmsconference paperInformática10.1007/978-3-319-00551-5_21open access171178Distributed Computing and Artificial Intelligence: 10th International ConferenceCC/0000021633