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Genetic algorithm in DNA computing: A solution to the maximal clique problem

机译:DNA计算中的遗传算法:最大派系问题的解决方案

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Genetic algorithm is one of the possible ways to break the limit of brute-force method in DNA computing. Using the idea of Darwinian evolution, we introduce a genetic DNA computing algorithm to solve the maximal clique problem. All the operations in the algorithm are accessible with today's molecular biotechnology. Our computer simulations show that with this new computing algorithm, it is possible to get a solution from a very small initial data pool, avoiding enumerating all candidate solutions. For randomly generated problems, genetic algorithm can give correct solution within a few cycles at high probability. Although the current speed of a DNA computer is slow compared with silicon computers, our simulation indicates that the number of cycles needed in this genetic algorithm is approximately a linear function of the number of vertices in the network. This may make DNA computers more powerfully attacking some hard computational problems.
机译:遗传算法是打破DNA计算中蛮力方法极限的一种可能方法。使用达尔文进化的思想,我们引入了一种遗传DNA计算算法来解决最大派系问题。当今的分子生物技术可以访问算法中的所有运算。我们的计算机仿真表明,使用这种新的计算算法,可以从很小的初始数据池中获得解决方案,而无需枚举所有候选解决方案。对于随机产生的问题,遗传算法可以在几个周期内以高概率给出正确的解决方案。尽管与硅计算机相比,DNA计算机的当前速度较慢,但​​我们的仿真表明,该遗传算法所需的循环数大约是网络中顶点数的线性函数。这可能会使DNA计算机更强大地攻击一些困难的计算问题。

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