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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Solving the Maximum Weighted Clique Problem Based on Parallel Biological Computing Model
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Solving the Maximum Weighted Clique Problem Based on Parallel Biological Computing Model

机译:基于并行生物计算模型的最大加权派系问题求解

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The maximum weighted clique (MWC) problem, as a typical NP-complete problem, is difficult to be solved by the electronic computer algorithm. The aim of the problem is to seek a vertex clique with maximal weight sum in a given undirected graph. It is an extremely important problem in the field of optimal engineering scheme and control with numerous practical applications. From the point of view of practice, we give a parallel biological algorithm to solve the MWC problem. For the maximum weighted clique problem withmedges andnvertices, we use fixed length DNA strands to represent different vertices and edges, fully conduct biochemical reaction, and find the solution to the MVC problem in certain length range withO(n2)time complexity, comparing to the exponential time level by previous computer algorithms. We expand the applied scope of parallel biological computation and reduce computational complexity of practical engineering problems. Meanwhile, we provide a meaningful reference for solving other complex problems.
机译:作为典型的NP完全问题,最大加权派系(MWC)问题很难通过电子计算机算法解决。该问题的目的是在给定的无向图中寻找具有最大权重总和的顶点团。在具有大量实际应用的最优工程方案和控制领域,这是一个极其重要的问题。从实践的角度来看,我们给出了一种并行的生物学算法来解决MWC问题。对于具有界和顶点的最大加权派系问题,我们使用固定长度的DNA链来表示不同的顶点和边缘,充分进行生化反应,并在一定长度范围内以O(n2)时间复杂度找到MVC问题的解决方案,与指数相比较时间级别由以前的计算机算法决定。我们扩展了并行生物学计算的应用范围,并减少了实际工程问题的计算复杂性。同时,为解决其他复杂问题提供了有意义的参考。

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