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ENC
2005
IEEE
13 years 10 months ago
Saving Evaluations in Differential Evolution for Constrained Optimization
Generally, evolutionary algorithms require a large number of evaluations of the objective function in order to obtain a good solution. This paper presents a simple approach to sav...
Efrén Mezura-Montes, Carlos A. Coello Coell...
GECCO
2010
Springer
176views Optimization» more  GECCO 2010»
13 years 7 months ago
A hierarchical cooperative evolutionary algorithm
To successfully search multiple coadaptive subcomponents in a solution, we developed a novel cooperative evolutionary algorithm based on a new computational multilevel selection f...
Shelly Xiaonan Wu, Wolfgang Banzhaf
EC
2012
289views ECommerce» more  EC 2012»
12 years 18 days ago
Multimodal Optimization Using a Bi-Objective Evolutionary Algorithm
In a multimodal optimization task, the main purpose is to find multiple optimal solutions (global and local), so that the user can have a better knowledge about different optima...
Kalyanmoy Deb, Amit Saha
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 6 months ago
Rank based variation operators for genetic algorithms
We show how and why using genetic operators that are applied with probabilities that depend on the fitness rank of a genotype or phenotype offers a robust alternative to the Sim...
Jorge Cervantes, Christopher R. Stephens
GECCO
2004
Springer
131views Optimization» more  GECCO 2004»
13 years 10 months ago
PolyEDA: Combining Estimation of Distribution Algorithms and Linear Inequality Constraints
Estimation of distribution algorithms (EDAs) are population-based heuristic search methods that use probabilistic models of good solutions to guide their search. When applied to co...
Jörn Grahl, Franz Rothlauf