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GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
14 years 11 months ago
A tree-based GA representation for the portfolio optimization problem
Recently, a number of works have been done on how to use Genetic Algorithms to solve the Portfolio Optimization problem, which is an instance of the Resource Allocation problem cl...
Claus de Castro Aranha, Hitoshi Iba
GECCO
2006
Springer
123views Optimization» more  GECCO 2006»
15 years 1 months ago
Fluctuating crosstalk, deterministic noise, and GA scalability
This paper extends previous work showing how fluctuating crosstalk in a deterministic fitness function introduces noise into genetic algorithms. In that work, we modeled fluctuati...
Paul Winward, David E. Goldberg
GECCO
2004
Springer
15 years 3 months ago
Introducing Subchromosome Representations to the Linkage Learning Genetic Algorithm
This paper introduces subchromosome representations to the linkage learning genetic algorithm (LLGA). The subchromosome representation is utilized for effectively lowering the num...
Ying-Ping Chen, David E. Goldberg
GECCO
2000
Springer
113views Optimization» more  GECCO 2000»
15 years 1 months ago
A Non-Linear Schema Theorem for Genetic Algorithms
We generalize Holland's Schema Theorem to the setting that genes are arranged, not necessarily in a linear sequence, but as the nodes in a connected graph. We have experiment...
William A. Greene
CEC
2005
IEEE
15 years 3 months ago
A quantitative approach for validating the building-block hypothesis
The building blocks are common structures of high-quality solutions. Genetic algorithms often assume the building-block hypothesis. It is hypothesized that the high-quality solutio...
Chatchawit Aporntewan, Prabhas Chongstitvatana