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ICGA
1993
96views Optimization» more  ICGA 1993»
13 years 6 months ago
Dynamic Control of Genetic Algorithms in a Noisy Environment
In this paper, we present e cient algorithms for adjusting con guration parameters of genetic algorithms that operate in a noisy environment. Assuming that the population size is ...
Akiko N. Aizawa, Benjamin W. Wah
GECCO
2006
Springer
220views Optimization» more  GECCO 2006»
13 years 8 months ago
A comparative study of immune system based genetic algorithms in dynamic environments
Diversity and memory are two major mechanisms used in biology to keep the adaptability of organisms in the everchanging environment in nature. These mechanisms can be integrated i...
Shengxiang Yang
GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
13 years 10 months ago
Coordinating multi-rover systems: evaluation functions for dynamic and noisy environments
This paper addresses the evolution of control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the perf...
Kagan Tumer, Adrian K. Agogino
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
13 years 8 months ago
Dominance learning in diploid genetic algorithms for dynamic optimization problems
This paper proposes an adaptive dominance mechanism for diploidy genetic algorithms in dynamic environments. In this scheme, the genotype to phenotype mapping in each gene locus i...
Shengxiang Yang
GECCO
2003
Springer
123views Optimization» more  GECCO 2003»
13 years 10 months ago
Benefits of Implicit Redundant Genetic Algorithms for Structural Damage Detection in Noisy Environments
A robust structural damage detection method that can handle noisy frequency response function information is discussed. The inherent unstructured nature of damage detection problem...
Anne M. Raich, Tamás Liszkai