摘要
针对蚁群算法局部搜索能力较弱,易于出现停滞和局部收敛、收敛速度慢,不能较好地应用于谐波平衡中的问题,提出了混合蚁群算法。该算法采用蚁群算法的全局搜索能力在全局中搜索初始最优解,利用拟牛顿算法较强的局部搜索能力逐步迭代,最终得到最优解。仿真结果表明:该算法与蚁群算法相比,迭代次数减少了45次,解的收敛可靠性增加了16.23%,同时仿真数据与实测数据拟合较好。混合算法兼顾了蚁群算法和拟牛顿法的优点,明显提高了收敛速度和解的收敛可靠性,克服了蚁群算法局部搜索能力差,收敛速度慢的缺点,对非线性分析具有较大的参考价值。
The local searching ability of the ant colony algorithm is weak, prone to appear stagnation and local convergence, convergence speed is slow, and could be not better applied to the harmonic balance,this paper proposed a hybrid ant colony algorithm. The algorithm firstly used the global search ability of ant colony algorithm as the initial optimal solution in the global search, by using the stronger local search ability of the quasi-newton algorithm for iteration step by step, ultimately getting the optimal solution. Simulation results show that compared with the ant colony algorithm, iterations times of the algorithm reduces by 45 times, convergence reliability of the solution increases by 16.23%, while the simulation data and measured data fitting better. Hybrid algorithm takes the advantages of ant colony algorithm and quasi-Newton method into account, significantly improves the convergence rate and reliability convergence of the solution, to overcome the weak local search ability of ant colony algorithm, the nonlinear circuit analysis has great reference value.
出处
《计算机应用研究》
CSCD
北大核心
2015年第11期3341-3344,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(61372058)
辽宁省高等学校优秀人才支持计划项目(LR2013012)
关键词
混合蚁群算法
拟牛顿
谐波平衡
非线性
hybrid ant colony algorithm
quasi-Newton method
harmonic balance
nonlinear