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SGA Implementation Using Integer Arrays for Storage of Binary Strings

机译:SGA实现使用整数阵列以存储二进制字符串

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The Simple Genetic Algorithm evaluates a group of binary strings on the basis of their fitness, performs crossover and mutation on them and tries to generate a group having maximum fitness. The usual method used for implementing the SGA is by using character arrays for storage of binary strings. But, this method has some disadvantages. The SGA implementation can be termed a success if the average fitness of the new generation is more than the initial average fitness. In this paper, we plan to implement the SGA using integer arrays for storage of binary strings. Then, we plan to compare the initial average fitness with the final average fitness so that the working of SGA can be verified. We have written the application such that varying population sizes can be given to check the correctness of the SGA algorithm.
机译:简单的遗传算法基于它们的健康来评估一组二进制字符串,在它们上执行交叉和突变,并试图生成具有最大健身的组。 用于实现SGA的通常方法是使用字符阵列来存储二进制字符串。 但是,这种方法有一些缺点。 如果新一代的平均适应性超过初始平均要素,则SGA实施可以取得成功。 在本文中,我们计划使用整数阵列来实现SGA以存储二进制字符串。 然后,我们计划将初始平均健康与最终平均健身进行比较,以便可以验证SGA的工作。 我们已经写了申请,以便可以给出不同的人口尺寸来检查SGA算法的正确性。

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