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CORR
2004
Springer
81views Education» more  CORR 2004»
13 years 4 months ago
Optimizing genetic algorithm strategies for evolving networks
This paper explores the use of genetic algorithms for the design of networks, where the demands on the network fluctuate in time. For varying network constraints, we find the best...
Matthew J. Berryman, Andrew Allison, Derek Abbott
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
13 years 8 months ago
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over t...
L. Darrell Whitley, Marc D. Richards, J. Ross Beve...
GECCO
2006
Springer
143views Optimization» more  GECCO 2006»
13 years 8 months ago
Heterogeneous cooperative coevolution: strategies of integration between GP and GA
Cooperative coevolution has proven to be a promising technique for solving complex combinatorial optimization problems. In this paper, we present four different strategies which i...
Leonardo Vanneschi, Giancarlo Mauri, Andrea Valsec...
GECCO
2010
Springer
254views Optimization» more  GECCO 2010»
13 years 9 months ago
Evolving viral marketing strategies
One method of viral marketing involves seeding certain consumers within a population to encourage faster adoption of the product throughout the entire population. However, determi...
Forrest Stonedahl, William Rand, Uri Wilensky
CORR
2008
Springer
129views Education» more  CORR 2008»
13 years 4 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,...