基于决策图贝叶斯优化进化算法的图K-划分算法

Graph K-Partitioning Algorithm based on DBOA

图K-划分问题是一种组合优化问题,可以归结为NP难题。针对该问题本文提出了一种基于决策图贝叶斯优化算法(Bayesian Optimization Algorithm with Decision Graphs,简称DBOA)的图K-划分, 该算法利用新的编码和解码方法以及适当的适应度函数来求解图K-划分问题。仿真结果表明了该算法的可行性和有效性。

Graph K-Partitioning is key technology in stream of information Partitioning in Compiling Optimization，it is NP hard problem. A Graph K-Partitioning algorithm based on DBOA（Bayesian Optimization Algorithm with Decision Graphs） is put forward for this problem, which utilizes new coding and decoding method and appropriate fitness function solving Graph K-Partitioning problem. The simulation results suggest that the scheme is feasible and effective。