Abstract. In this paper, we propose an approach for solving hierarchical multi-objective optimization problems (MOPs). In realistic MOPs, two main challenges have to be considered:...
This paper proposes a novel adaptive representation for evolutionary multiobjective optimization for solving a stock modeling problem. The standard Pareto Achieved Evolution Strat...
Mihai Oltean, Crina Grosan, Ajith Abraham, Mario K...
Despite the existence of a number of procedures for real-parameter optimization using evolutionary algorithms, there is still a need of a systematic and unbiased comparison of diļ...
An evolutionary algorithm is used to design a ļ¬nite impulse response digital ļ¬lter with reduced power consumption. The proposed design approach combines genetic optimization an...
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed ...