一种求解TSP的Beam-PSO算法

A Kind of BEAM-PSO Algorithm for TSP

为了求解大规模高复杂度的TSP问题,文中基于标准粒子群算法的框架,构建了Beam-PSO混合优化算法.利用BeamSearch优化技术进一步强化标准PSO算法的深度开发能力,进而强化的标准PSO算法的优化性能.采用TSP标准数据集并通过Matlab仿真测试,与其他算法进行对比,该算法获得的最优解更接近于已知最优解,且多次优化结果的均值更小证明该算法的搜索性能较强,能够有效地应对离散优化问题.

In order to solve the large-scale and high-complexity TSP problem, the Beam-PSO hybrid optimization algorithm was constructed based on the framework of the standard particle swarm optimization algorithm. Beam Search optimization technology was used to strengthen the in-depth development capability of the standard PSO algorithm and further strengthen the optimization performance of the standard PSO algorithm. Compared with other algorithms, TSP standard data set was adopted and Matlab simulation tests were carried out. The optimal solution obtained by the algorithm is closer to the known optimal solution, and the average value of multiple optimization results is smaller. It is proved that the algorithm has strong search performance and can effectively deal with discrete optimization problems.