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» A Grid-Oriented Genetic Algorithm
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AIR
2005
130views more  AIR 2005»
13 years 9 months ago
Framework for Task Scheduling in Heterogeneous Distributed Computing Using Genetic Algorithms
An algorithm has been developed to dynamically schedule heterogeneous tasks on heterogeneous processors in a distributed system. The scheduler operates in an environment with dynam...
Andrew J. Page, Thomas J. Naughton
GECCO
2007
Springer
167views Optimization» more  GECCO 2007»
14 years 3 months ago
An improved restricted growth function genetic algorithm for the consensus clustering of retinal nerve fibre data
This paper describes an extension to the Restricted Growth Function grouping Genetic Algorithm applied to the Consensus Clustering of a retinal nerve fibre layer data-set. Consens...
Stephen Swift, Allan Tucker, Jason Crampton, David...
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
13 years 10 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
GECCO
2000
Springer
170views Optimization» more  GECCO 2000»
14 years 1 months ago
A Comparison of Genetic Algorithms for the Dynamic Job Shop Scheduling Problem
The majority of the research using evolutionary algorithms for the Job Shop Scheduling Problem (JSSP) has studied only the static JSSP. Few evolutionary algorithms have been appli...
Manuel Vázquez, L. Darrell Whitley
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
13 years 10 months ago
Dual-population genetic algorithm for nonstationary optimization
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Taejin Park, Ri Choe, Kwang Ryel Ryu