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Multiobjective Genetic Algorithm for Minimum Weight Minimum Connected Dominating Set

机译:用于最小重量最小连接主导集的多目标遗传算法

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Connected Dominating Set (CDS) is a connected subgraph of a graph G with the property that any given node in G either belongs to the CDS or is adjacent to one of the CDS nodes. Minimum Connected Dominating Sets (MCDS), where the CDS nodes are sought to be minimized, are of special interests in various fields like Computer networks, Biological networks, Social networks, etc., since they represent a set of minimal important nodes. Similarly, Minimum Weight Connected Dominating Sets (MWCDS), where the connected weights among the CDS nodes are sought to be minimized, is also of interest in many research application. This work is based on the hypothesis that a CDS with both the properties of minimum size and minimum weight optimized would enhance performance in many applications where CDS is used. Though there are a good number of approximate and heuristic algorithms for MCDS and MWMCDS, there is no work to the best of our knowledge, that optimizes the generated CDS with respect to both the size and weight. A Multiobjective Genetic Algorithm for Minimum Weight Minimum Connected Dominating Set (MOGA-MWMCDS) is proposed. Performance analysis based on a Wireless Sensor Network (WSN) scenario indicates the efficiency of the proposed MOGA-MWMCDS and supports the advantage of MWMCDS use.
机译:连接的主导集(CD)是图G的连接子图,其中具有G的任何给定节点属于CD或与其中一个CD节点相邻。最小连接的主导集(MCD),其中寻求最小化CD节点,在计算机网络,生物网络,社交网络等中的各个领域具有特殊兴趣,因为它们代表了一组最小的重要节点。类似地,寻求最小化CD节点之间的连接权重的最小权重连接的主导集合(MWCD),其在许多研究应用中也感兴趣。这项工作基于假设,即CDS具有最小尺寸和最小重量的性能,优化的性能将增强在使用CD的许多应用中的性能。虽然MCD和MWMCDS存在良好的近似和启发式算法,但我们的知识没有工作,虽然我们的知识没有工作,但是在尺寸和重量方面优化产生的CD。提出了一种用于最小重量最小连接的主导集合(MOGA-MWMCD)的多目标遗传算法。基于无线传感器网络(WSN)方案的性能分析表明所提出的MOGA-MWMCDS的效率并支持MWMCDS使用的优势。

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