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Multiobjective Optimization Using Ideas from the Clonal Selection Principle
Nareli Cruz Cortés and Carlos A. Coello Coello
CINVESTAV-IPN
Evolutionary Computation Group
Depto. de Ingeniería Eléctrica
Sección de Computación
Av. Instituto Politécnico Nacional No. 2508
Col. San Pedro Zacatenco
México, D. F. 07300, MEXICO
nareli@computacion.cs.cinvestav.mx,
ccoello@cs.cinvestav.mx
Abstract. In this paper, we propose a new multiobjective optimization approach based on the clonal selection principle. Our approach is compared with respect to other evolutionary multiobjective optimization techniques that are representative of the state-of-the-art in the area. In our study, several test functions and metrics commonly adopted in evolutionary multiobjective optimization are used. Our results indicate that the use of an artificial immune system for multiobjective optimization is a viable alternative.
LNCS 2723, p. 158 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003