【摘要】 针对模拟退火算法收敛速度慢这一缺点 ,提出了一种基于模拟退火算法和复合形法相结合的新型混合优化算法 ,并成功应用于机器人神经网络路径规划中。该算法不仅继承了模拟退火算法能得到全局最优解的优点 ,又能搜索到理想的下降方向 ,提高了算法的收敛速度。仿真实验研究表明 :这种新型混合优化算法 ,计算简单 ,收敛速度快 ,初值鲁棒性好更多还原

【Abstract】 Aimed at the defect of low convergent speed in algorithm of simulated annealing and based on a kind of combination of simulated annealing a lgorithm and compound shape method,a new mixed optimal algorithm was put forward and being applied successfully to path planning of robotic neural network.This algorithm could not only carry forward the advantage of simulated annealing algo rithm for obtaining the overall optimal solution,but also search out the ideal d escending direction,thus raised the convergent speed of the algorithm.The simula tive experiment demonstrates that this new kind of mixed optimal algorithm is si mple in computation,rapid in convergent speed and good in robustness of initial value.更多还原