Optimización de Enjambre de Partículas para Problemas de Muchos Objetivos
Mateo Torres Bobadilla$^{1}$, Benjamín Barán$^{2}$
$^{1}$Universidad Católica “Nuestra Señora de la Asunción”. Asuncion Paraguay,
$^{2}$Universidad Nacional del Este. Ciudad del Este Paraguay
email: torresmateo@gmail.com, bbaran@cba.com.py

Schedule:Mon 19th@10:15, Room: A

The difficulty to solve problems with many, possibly conflicting, objectives logically increases with the number of objectives, what makes them difficult to solve using multi-objective algorithms like the well known NSGA-II. Therefore, this work proposes the use of a particle swarm optimization (PSO) algorithm to solve many-objective problems. The main premise of this work is that MOPSO may be a good option for solving many-objective problems, presenting experimental evidence that supports this premise using the well known DTLZ benchmark with different performance metrics such as hypervolume, coverage and generational distance, among others.

BibTex

@InProceedings{CLEI-2015:142608,
	author 		= {Mateo Torres Bobadilla and Benjamín Barán},
	title 		= {Optimización de Enjambre de Partículas para Problemas de Muchos Objetivos},
	booktitle 	= {2015 XLI Latin American Computing Conference (CLEI)},
	pages 		= {238--248},
	year 		= {2015},
	editor 		= {Hector Cancela and Alex Cuadros-Vargas and Ernesto Cuadros-Vargas},
	address 	= {Arequipa-Peru},
	month 		= {October},
	organization 	= {CLEI},
	publisher 	= {CLEI},
	url 		= {http://clei.org/clei2015/142608},
	isbn 		= {978-1-4673-9143-6},
	}