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EMO
2005
Springer
110views Optimization» more  EMO 2005»
14 years 3 months ago
Parallelization of Multi-objective Evolutionary Algorithms Using Clustering Algorithms
Abstract. While Single-Objective Evolutionary Algorithms (EAs) parallelization schemes are both well established and easy to implement, this is not the case for Multi-Objective Evo...
Felix Streichert, Holger Ulmer, Andreas Zell
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
14 years 1 months ago
Combining gradient techniques for numerical multi-objective evolutionary optimization
Recently, gradient techniques for solving numerical multi
Peter A. N. Bosman, Edwin D. de Jong
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
14 years 3 months ago
Inverse multi-objective robust evolutionary design optimization in the presence of uncertainty
In many real-world design problems, uncertainties are often present and practically impossible to avoid. Many existing works on Evolutionary Algorithm (EA) for handling uncertaint...
Dudy Lim, Yew-Soon Ong, Bu-Sung Lee
GECCO
2008
Springer
199views Optimization» more  GECCO 2008»
13 years 11 months ago
Analysis of multi-objective evolutionary algorithms to optimize dynamic data types in embedded systems
New multimedia embedded applications are increasingly dynamic, and rely on Dynamically-allocated Data Types (DDTs) to store their data. The optimization of DDTs for each target em...
José Ignacio Hidalgo, José L. Risco-...
CEC
2009
IEEE
14 years 4 months ago
Performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on the CEC09 test problems
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...