A Kind of BEAM-PSO Algorithm Solving TSP

Q. Song
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Abstract

In order to solve the TSP problem with large scale and high complexity, 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 further enhance the deep development capability of standard PSO algorithm, in order to enhance the optimization performance of standard PSO algorithm. TSP standard data set and Matlab simulation test were adopted to compare with other algorithms. The algorithm’s optimal solution was closer to the known optimal solution, and the average value of multiple optimization results was smaller, proving that this algorithm had strong search performance and could effectively deal with discrete optimization problems.
一种求解TSP的波束粒子群算法
为了解决大规模、高复杂度的TSP问题,在标准粒子群优化算法框架的基础上,构建了波束-粒子群优化算法。采用波束搜索优化技术,进一步增强标准粒子群算法的深度开发能力,从而提高标准粒子群算法的优化性能。采用TSP标准数据集和Matlab仿真测试与其他算法进行比较。该算法的最优解更接近已知最优解,且多个优化结果的平均值更小,证明该算法具有较强的搜索性能,能够有效地处理离散优化问题。
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