井冈山大学学报（自然科学版）2025，Vol.46Issue(5)：80-90,11.DOI:10.3969/j.issn.1674-8085.2025.05.010
改进遗传算法在路径规划中的应用研究
THE APPLICATION RESEARCH OF IMPROVED GENETIC ALGORITHM IN PATH PLANNING
摘要
Abstract
Aiming at the problems of excessive path deviation,slow convergence speed,and susceptibility to local optima in traditional genetic algorithms for path planning,an improved genetic algorithm is proposed in this paper.By initializing an improved population by connecting two paths end-to-end through a median transition point,an excellent initial population is generated to improve the search efficiency in the early stages.Adopting an improved tournament selection strategy and proposing a simulated annealing method is done to prevent falling into local optima and improve search capability.Adaptive crossover and mutation probability functions are designed to enhance convergence speed and population diversity.Additionally,improved multi-point crossover and multiple mutation strategies are employed to improve the quality and stability of path planning solutions.Simulation results demonstrate that,compared with the traditional genetic algorithms,the improved guided-following genetic algorithm,improved adaptive genetic algorithm,multi-population adaptive ant algorithm,and improved catastrophic mutation genetic algorithm,the proposed improved genetic algorithm can enhance the convergence speed,reduce the number of path deflections,and path length,so as to search the more optimal paths.关键词
路径规划/遗传算法/自适应交叉策略/自适应变异策略/模拟退火算法Key words
path planning/genetic algorithm/adaptive crossover strategy/adaptive mutation strategy/simulated annealing algorithm分类
信息技术与安全科学引用本文复制引用
张泽宇,王雷,寿林,夏强强..改进遗传算法在路径规划中的应用研究[J].井冈山大学学报（自然科学版）,2025,46(5):80-90,11.基金项目
国家自然科学基金项目(51305001) （51305001）
安徽省高校优秀拔尖人才培育项目(gxbjZD2022023) （gxbjZD2022023）
安徽省高校自然科学研究重点项目(2023AH050935) （2023AH050935）
安徽省机器视觉检测与感知重点实验室开放基金项目(KLMVI-2024-HIT-15) （KLMVI-2024-HIT-15）
