Clustering algorithm based on genetic simulated an
2016-08-23
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Genetic algorithms individual difference in the early running when using the classic roulette mode selection, the number of offspring produced and father fitness is proportional to the size, so early offspring full of easy to make good of individuals, populations, causing premature. Later in the genetic algorithm, Adaptive convergence when best individual result in offspring, obvious advantages, so that the entire population and evolutionary stagnation. The fitness is necessary for proper stretching, so that when the temperature is high (pre-GA), similar to meet similar individuals produce offspring probability; after declining when temperatures, tensile strengthen, making similar Fitness Fitness difference amplifier, which makes the best individual advantage is more obvious. Due to simulated annealing and genetic algorithms can learn from each other, thus effectively overcomes the premature phenomena of genetic algorithms, and designed according to the clustering of specific genetic e
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