Performance Analysis of Memetic algorithm Using VIKOR Method

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Abstract

A memetic algorithm is a variant of the traditional genetic algorithm is expansion. This is a local search technique Uses, which are pre-merged Reduces chance. A simplified data Cryptographic analysis of an encryption standard is NP-hard Can be formulated as a joint problem. Memetic algorithms (MAs) are global search Evolution uses local search rather than algorithms are the means. MAs are evolutionary mechanisms are, they are local search to refine individuals using processes. Dolphins, Elegans, Hamsterster, Ca-Grqc. The size of population, the number of generations, Size of the mating pool, Tournament size, the probability of crossover, the probability of mutation. From the end based on the number of generations are the result seen and got the first Rank, whereas the probability of mutation got having the lowest rank. The Value of dataset for Memetic Algorithm in VIKOR method shows that it results in the number of generations and top ranking.
基于VIKOR方法的模因算法性能分析
模因算法是传统遗传算法的一种扩展。这是一种局部搜索技术,它是预先合并的,减少了机会。一个加密标准的简化数据加密分析是NP-hard的,可以表述为一个联合问题。模因算法(Memetic algorithms, MAs)是一种全局搜索算法,进化使用局部搜索而不是算法作为手段。MAs是进化机制,它们是局部搜索,通过过程来完善个体。海豚、Elegans、仓鼠、Ca-Grqc。种群的规模,世代的数量,交配池的规模,比赛的规模,交叉的概率,突变的概率。从最后根据代数得出的结果来看,得到的是排名第一的,而得到的变异概率是排名最低的。模因算法在VIKOR方法中的数据集值表明,它的结果是代数和最高排名。
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