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An accelerated Genetic Algorithm
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DOI：10.1023/A:1008227606285.png)
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摘要
En 中文
The standard Genetic Algorithm, originally inspired by natural evolution, has displayed its effectiveness in solving a wide variety of complex problems. This paper describes the use of the natural phenomenon known as the Baldwin effect (or cross-generational learning) as an enhancement to the standard Genetic Algorithm. This is implemented by using an artificial neural network to store aspects of the population's history. It also describes a method by which the negative side effects of a large elite sub-population can be counter-balanced by using an ageing coefficient in the fitness calculation.
Keyword:
genetic algorithm
neural networks
Baldwin effect
optimisation
history
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