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GECCO
2008
Springer
144views Optimization» more  GECCO 2008»
15 years 8 months ago
Maintaining diversity through adaptive selection, crossover and mutation
This paper presents an Adaptive Genetic Algorithm (AGA) where selection pressure, crossover and mutation probabilities are adapted according to population diversity statistics. Th...
Brian McGinley, Fearghal Morgan, Colm O'Riordan
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
15 years 8 months ago
An EDA based on local markov property and gibbs sampling
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
Siddhartha Shakya, Roberto Santana
GECCO
2008
Springer
154views Optimization» more  GECCO 2008»
15 years 8 months ago
Genetic algorithms for self-spreading nodes in MANETs
We present a force-based genetic algorithm for self-spreading mobile nodes uniformly over a geographical area. Wireless mobile nodes adjust their speed and direction using a genet...
Cem Safak Sahin, Elkin Urrea, M. Ümit Uyar, M...
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 8 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
2008
Springer
324views Optimization» more  GECCO 2008»
15 years 8 months ago
Convergence behavior of the fully informed particle swarm optimization algorithm
The fully informed particle swarm optimization algorithm (FIPS) is very sensitive to changes in the population topology. The velocity update rule used in FIPS considers all the ne...
Marco Antonio Montes de Oca, Thomas Stützle
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