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» Performance comparison of memetic algorithms
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PR
2008
131views more  PR 2008»
13 years 7 months ago
A memetic algorithm for evolutionary prototype selection: A scaling up approach
Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. ...
Salvador García, José Ramón C...
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
14 years 1 months ago
Enhancing differential evolution performance with local search for high dimensional function optimization
In this paper, we proposed Fittest Individual Refinement (FIR), a crossover based local search method for Differential Evolution (DE). The FIR scheme accelerates DE by enhancing...
Nasimul Noman, Hitoshi Iba
CEC
2007
IEEE
14 years 1 months ago
A study on the design issues of Memetic Algorithm
— Over the recent years, there has been increasing research activities made on improving the efficacy of Memetic Algorithm (MA) for solving complex optimization problems. Partic...
Q. H. Nguyen, Yew-Soon Ong, Natalio Krasnogor
CEC
2010
IEEE
13 years 8 months ago
Classifier-assisted constrained evolutionary optimization for automated geometry selection of orthodontic retraction spring
In orthodontics, retraction springs made of metallic wires are often used to move a tooth with respect to another by the virtue of the spring back effect. Specially selected form o...
Dudy Lim, Yew-Soon Ong, Rachman Setiawan, Muhammad...
AEI
2005
99views more  AEI 2005»
13 years 7 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