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EMO
2003
Springer
81views Optimization» more  EMO 2003»
14 years 2 months ago
Solving Hierarchical Optimization Problems Using MOEAs
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:...
Christian Haubelt, Sanaz Mostaghim, Jürgen Te...
ISDA
2005
IEEE
14 years 2 months ago
Multiobjective Optimization Using Adaptive Pareto Archived Evolution Strategy
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...
CEC
2005
IEEE
14 years 3 months ago
A population-based, steady-state procedure for real-parameter optimization
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...
Ankur Sinha, Santosh Tiwari, Kalyanmoy Deb
EUROGP
2001
Springer
124views Optimization» more  EUROGP 2001»
14 years 1 months ago
An Evolutionary Approach to Automatic Generation of VHDL Code for Low-Power Digital Filters
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...
Massimiliano Erba, Roberto Rossi, Valentino Libera...
AEI
2005
99views more  AEI 2005»
13 years 9 months ago
Comparison among five evolutionary-based optimization algorithms
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 ...
Emad Elbeltagi, Tarek Hegazy, Donald E. Grierson