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CEC
2005
IEEE

Genetic algorithms with self-organized criticality for dynamic optimization problems

12 years 3 months ago
Genetic algorithms with self-organized criticality for dynamic optimization problems
This paper proposes a genetic algorithm (GA) with random immigrants for dynamic optimization problems where the worst individual and its neighbours are replaced every generation. In this GA, the individuals interact with each other and, when their fitness is close, as in the case where the diversity level is low, one single replacement can affect a large number of individuals. This simple approach can take the system to a kind of self-organization behavior, known as SelfOrganized Criticality (SOC), which is useful to maintain the diversity of the population in dynamic environments and hence allows the GA to escape from local optima when the problem changes. The experimental results show that the proposed GA presents the phenomenon of SOC.
Renato Tinós, Shengxiang Yang
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where CEC
Authors Renato Tinós, Shengxiang Yang
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