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EMO
2003
Springer
81views Optimization» more  EMO 2003»
15 years 3 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
15 years 3 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
15 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»
15 years 2 months ago
An Evolutionary Approach to Automatic Generation of VHDL Code for Low-Power Digital Filters
An evolutionary algorithm is used to design a finite impulse response digital filter with reduced power consumption. The proposed design approach combines genetic optimization an...
Massimiliano Erba, Roberto Rossi, Valentino Libera...
AEI
2005
99views more  AEI 2005»
14 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