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针对现有优化算法求解旅行商问题(TSP)时易早熟收敛的缺陷,提出一种求解TSP问题的改进蛙跳算法.在基本蛙跳算法的基础上,通过在局部搜索过程中设计置换元素和分块重组这两种青蛙个体的更新策略,从而增大了搜索空间,提高了搜索效率;在全局信息交换过程中引入打开交叉线策略和邻域调整策略进行局部优化,从而提高算法跳出局部极值的能力.最后对TSPLIB中的8个实例进行了仿真实验,实验结果表明,本文算法是有效且精度较高的.这也为蛙跳算法和TSP问题的研究提供了新的途径和手段.
Aiming at the shortcomings of existing optimization algorithms in solving the premature convergence problem of traveling salesman problem (TSP), an improved leapfrogging algorithm for solving TSP problem is proposed.Based on the basic leapfrogging algorithm, by designing replacement elements in local search process and Block reorganization of the two frog individual update strategy, thereby increasing the search space and improve the search efficiency; the introduction of the global information exchange process to open the cross line strategy and neighborhood adjustment strategy for local optimization, thereby increasing the algorithm out of the local pole The experimental results show that the proposed algorithm is effective and accurate.It also provides a new way and means for the research of frolic leap algorithm and TSP problem.