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GECCO
2004
Springer
126views Optimization» more  GECCO 2004»
14 years 1 months ago
A Gene Based Adaptive Mutation Strategy for Genetic Algorithms
In this study, a new mechanism that adapts the mutation rate for each locus on the chromosomes, based on feedback obtained from the current population is proposed. Through tests us...
Sima Uyar, Sanem Sariel, Gülsen Eryigit
GECCO
2000
Springer
114views Optimization» more  GECCO 2000»
13 years 11 months ago
Intelligent Recombination Using Individual Learning in a Collective Learning Genetic Algorithm
This paper introduces a new collective learning genetic algorithm (CLGA) which employs individual learning to do intelligent recombination based on a cooperative exchange of knowl...
Terry P. Riopka, Peter Bock
HEURISTICS
2010
13 years 2 months ago
An evolutionary and constructive approach to a crew scheduling problem in underground passenger transport
Operation management of underground passenger transport systems is associated with combinatorial optimization problems (known as crew and train scheduling and rostering) which bel...
Rafael Elizondo, Víctor Parada, Lorena Prad...
CEC
2007
IEEE
14 years 1 months ago
Convergence and rate of convergence of a foraging ant model
— We present an ant model that solves a discrete foraging problem. We describe simulations and provide a complete convergence analysis: we show that the ant population computes t...
Amine M. Boumaza, Bruno Scherrer
GECCO
2008
Springer
324views Optimization» more  GECCO 2008»
13 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