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EMO
2005
Springer
110views Optimization» more  EMO 2005»
13 years 12 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»
13 years 10 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»
13 years 12 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 7 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 1 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...