[1]杨四海.多障碍离散路径规划的遗传算法求解[J].华侨大学学报(自然科学版),2006,27(3):317-320.[doi:10.3969/j.issn.1000-5013.2006.03.026]
　Yang Sihai.Path Planning in the Environment Containing Large Numbers of Obstacles Using Genetic Algorithm[J].Journal of Huaqiao University(Natural Science),2006,27(3):317-320.[doi:10.3969/j.issn.1000-5013.2006.03.026]
点击复制

多障碍离散路径规划的遗传算法求解()
分享到：

《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第27卷
期数:
2006年第3期
页码:
317-320
栏目:
出版日期:
2006-07-20

文章信息/Info

Title:
Path Planning in the Environment Containing Large Numbers of Obstacles Using Genetic Algorithm
文章编号:
1000-5013(2006)03-0317-04
作者:
杨四海
华侨大学信息科学与工程学院 福建泉州362021
Author(s):
Yang Sihai
College of Information Science and Engineering, Huaqiao University, 362021, Quanzhou, China
关键词:
路径规划;  遗传算法;  迷宫问题;  变异算子
Keywords:
path planning;  genetic algorithm;  labyrinth;  mutation operator
分类号:
O221
DOI:
10.3969/j.issn.1000-5013.2006.03.026
文献标志码:
A
摘要:
使用遗传算法求解多障碍离散路径规划问题时,容易产生大量无效解.通过计算个体的有效路径,评价个体,并在遗传操作中不断累积局部优势模式,可以对无效解进行遗传操作并最终生成有效解.无效解往往在有效路径的尾部陷入障碍.针对此变异操作,使得个体不仅可以保留前端累积的局部优势模式,同时可通过尾部变异跳出环境障碍.
Abstract:
It is very easy to generate a mass of invalid solution while solving path planning in environment containing large numbers of obstacles using genetic algorithm.By computing valid path to evaluate individuals and cumulate local advantage modules in the procedure of genetic operations,invalid individuals can be processed and formed valid individuals at last.Because invalid individuals are always barricaded in the end of its chromosomes,end-mutation is proposed to solve this problem.Simulation results show the validity of this method.

参考文献/References:

[1] 梁晓辉, 吴威, 赵沁平. 大规模真实地形数据中的全局路径规划方法--基于遗传算法的研究 [J]. 计算机研究与发展, 2002(3):301-306.
[2] 罗熊, 樊晓平, 易晟. 具有大量不规则障碍物的环境下机器人路径规划的一种新型遗传算法 [J]. 机器人, 2004(1):11-16.doi:10.3321/j.issn:1002-0446.2004.01.003.
[3] 冯文镛, 杨灿军, 陈鹰. ACR原型系统的全局路径规划遗传算法的研究 [J]. 控制理论与应用, 2002(4):282-286.doi:10.3969/j.issn.1000-8152.2002.02.030.
[4] 王斌, 李元香. 用遗传算法解迷宫问题 [J]. 微型机与应用, 2002, (10):58-60.doi:10.3969/j.issn.1674-7720.2002.10.022.
[5] 孙树栋, 曲彦宾. 遗传算法在机器人路径规划中的应用研究 [J]. 西北工业大学学报, 1998(2):79-83.
[6] Gen M, Cheng R. Genetic algorithm and Engineering design [M]. New York:Wiley, 1977.134-140.
[7] 刘志宏, 施工, 胡永明. 一种新的全局优化算法--统计归纳算法 [J]. 清华大学学报(自然科学版), 2002(5):580-583.doi:10.3321/j.issn:1000-0054.2002.05.005.

相似文献/References:

[1]范慧琳.机器学习的若干方法分析[J].华侨大学学报(自然科学版),1995,16(1):116.[doi:10.11830/ISSN.1000-5013.1995.01.0116]
　Fan Huilin.An Analysis of Several Methods of Machine Learning[J].Journal of Huaqiao University(Natural Science),1995,16(3):116.[doi:10.11830/ISSN.1000-5013.1995.01.0116]
[2]郑力新.采用遗传算法的模拟集成电路参数最优设计[J].华侨大学学报(自然科学版),1998,19(2):128.[doi:10.11830/ISSN.1000-5013.1998.02.0128]
　Zheng Lixin.Parameter Optimization Design of Analog Integrated Circuit by Adopting Genetic Algorithm[J].Journal of Huaqiao University(Natural Science),1998,19(3):128.[doi:10.11830/ISSN.1000-5013.1998.02.0128]
[3]周凯汀,郑力新.基于遗传算法的PID参数优化设计[J].华侨大学学报(自然科学版),2000,21(2):200.[doi:10.3969/j.issn.1000-5013.2000.02.022]
　Zhou Kaitin,Zheng Lixin.Optimization Design Based on Genetic Algorithm for Designing Parameters of PID controller[J].Journal of Huaqiao University(Natural Science),2000,21(3):200.[doi:10.3969/j.issn.1000-5013.2000.02.022]
[4]梅余霞,谢晓兰,万宁,等.木糖醇发酵液脱色的优化工艺[J].华侨大学学报(自然科学版),2000,21(4):394.[doi:10.3969/j.issn.1000-5013.2000.04.014]
　Mei Yuxia,Xie Xiaolan,Wan Ning,et al.Technology for Optimizing Decoloration of Xylitol Fermentation Liquor[J].Journal of Huaqiao University(Natural Science),2000,21(3):394.[doi:10.3969/j.issn.1000-5013.2000.04.014]
[5]任兴仑,童昕.压电智能梁振动控制的遗传算法优化设计[J].华侨大学学报(自然科学版),2002,23(1):81.[doi:10.3969/j.issn.1000-5013.2002.01.018]
　Ren Xinglun,Tong Xin.Optimal Control of Vibration Control of Piezoelectric Intelligent Beam Based on Genetic Algorithm[J].Journal of Huaqiao University(Natural Science),2002,23(3):81.[doi:10.3969/j.issn.1000-5013.2002.01.018]
[6]郑力新,黄东海,周凯汀.采用遗传算法实现时域模型降阶[J].华侨大学学报(自然科学版),2003,24(2):143.[doi:10.3969/j.issn.1000-5013.2003.02.006]
　Zheng Lixin,Huang Donghai,Zhou Kaiting.Realizing Reduction of Time Domain Model by Adopting Genetic Algorithm[J].Journal of Huaqiao University(Natural Science),2003,24(3):143.[doi:10.3969/j.issn.1000-5013.2003.02.006]
[7]徐玉野,王全凤,罗漪.摩擦耗能支撑参数优化[J].华侨大学学报(自然科学版),2004,25(1):45.[doi:10.3969/j.issn.1000-5013.2004.01.012]
　Xu Yuye,Wang Quanfeng,Luo Yi.Parameter Optimization with Frictional Energy Dissipation as a Brace[J].Journal of Huaqiao University(Natural Science),2004,25(3):45.[doi:10.3969/j.issn.1000-5013.2004.01.012]
[8]宋海洲.生产函数中参数估计方法的进一步改进[J].华侨大学学报(自然科学版),2005,26(1):23.[doi:10.3969/j.issn.1000-5013.2005.01.006]
　Song Haizhou.Further Improvement of the Method for Estimating Parameters in Production Function[J].Journal of Huaqiao University(Natural Science),2005,26(3):23.[doi:10.3969/j.issn.1000-5013.2005.01.006]
[9]方千山.模糊遗传算法的自适应PID控制器[J].华侨大学学报(自然科学版),2005,26(1):38.[doi:10.3969/j.issn.1000-5013.2005.01.010]
　Fang Qianshan.Adaptive PID Controller Based on Fuzzy Genetic Algorithm[J].Journal of Huaqiao University(Natural Science),2005,26(3):38.[doi:10.3969/j.issn.1000-5013.2005.01.010]
[10]周凯汀,郑力新.进化算法的PID参数最优设计[J].华侨大学学报(自然科学版),2005,26(1):85.[doi:10.3969/j.issn.1000-5013.2005.01.022]
　Zhou kaiting,Zheng Lixin.Optimal Design of PID Parameters by Evolution Algorithm[J].Journal of Huaqiao University(Natural Science),2005,26(3):85.[doi:10.3969/j.issn.1000-5013.2005.01.022]

备注/Memo

备注/Memo:
福建省自然科学基金资助项目(A0540005)
更新日期/Last Update: 2014-03-23