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Efficient and Reliable Evolutionary Multiobjective Optimization Using 
-Dominance Archiving and Adaptive Population Sizing
Venkat Devireddy and Patrick Reed
Department of Civil and Environmental Engineering, 212 Sackett Building, University Park, PA-16802vkd106@psu.edu
preed@engr.psu.edu
Abstract. This paper introduces a new algorithm, termed as the 
-NSGA-II that enables the user to specify the precision with which they want to quantify the Pareto optimal set and all other parameters are automatically specified within the algorithm. The development of the -NSGA-II was motivated by the steady state -MOEA developed by Deb et al. [3]. The next section briefly describes the -NSGA-II.
LNCS 3103, p. 390 f.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2004