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GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
15 years 1 months ago
Adaptive discretization for probabilistic model building genetic algorithms
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization pro...
Chao-Hong Chen, Wei-Nan Liu, Ying-Ping Chen
CCE
2005
14 years 9 months ago
Use of parallel computers in rational design of redundant sensor networks
A general method to design optimal redundant sensor network even in the case of one sensor failure and able to estimate process key parameters within a required accuracy is propos...
Carine Gerkens, Georges Heyen
CEC
2008
IEEE
15 years 4 months ago
A contour method in population-based stochastic algorithms
—Inspired by the contours in topography, this paper proposes a contour method for the population-based stochastic algorithms to solve the problems with continuous variables. Rely...
Ying Lin, Jun Zhang, Lu-kai Lan
CORR
2008
Springer
129views Education» more  CORR 2008»
14 years 9 months ago
Evolving Dynamic Change and Exchange of Genotype Encoding in Genetic Algorithms for Difficult Optimization Problems
The application of genetic algorithms (GAs) to many optimization problems in organizations often results in good performance and high quality solutions. For successful and efficien...
Maroun Bercachi, Philippe Collard, Manuel Clergue,...
IPPS
2006
IEEE
15 years 3 months ago
A parallel memetic algorithm applied to the total tardiness machine scheduling problem
This work proposes a parallel memetic algorithm applied to the total tardiness single machine scheduling problem. Classical models of parallel evolutionary algorithms and the gene...
Vinícius Garcia, Paulo M. França, Al...