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基于遗传模拟退火算法的静态路径规划研究
引用本文:黄席樾,蒋卓强. 基于遗传模拟退火算法的静态路径规划研究[J]. 重庆理工大学学报(自然科学版), 2007, 21(6): 53-57,121
作者姓名:黄席樾  蒋卓强
作者单位:重庆大学自动化学院 重庆400044
摘    要:针对传统遗传算法在基于神经网络模型的移动机器人静态路径规划中求解最优路径时存在的收敛较慢、易陷入局部极值点的问题,提出了一种基于遗传模拟退火算法的静态路径规划方法.通过对算法进行实验仿真,结果表明提出的静态路径规划方法是正确有效的.

关 键 词:路径规划  遗传算法  模拟退火算法  神经网络
文章编号:1671-0924(2007)06-0053-05
修稿时间:2007-03-25

Path Planning in a Static Environment Based on Genetically Simulated Annealing Algorithm
HUANG Xi-yue,JIANG Zhuo-qiang. Path Planning in a Static Environment Based on Genetically Simulated Annealing Algorithm[J]. Journal of Chongqing University of Technology(Natural Science), 2007, 21(6): 53-57,121
Authors:HUANG Xi-yue  JIANG Zhuo-qiang
Abstract:In finding the best path in a static environment based on neural network by means of genetic algorithm,there are such problems as slow convergent speed and premature.The paper proposes a method of path planning based on genetically simulated annealing algorithm.The simulation results from experimental simulation of this algorithm show that the proposed method is correct and effective.
Keywords:path planning  genetic algorithm  simulated annealing algorithm  neural network
本文献已被 CNKI 等数据库收录!
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