摘要
针对传统蚁群算法在前期搜索盲目性大、拐点多等问题,对蚁群算法进行以下改进。首先,为了增强目标位置的启发信息,引入距离增益系数,将目标位置对下一个待选栅格节点的影响进行放大;然后引入带有权重的距离启发因子,在状态转移概率中加入距离启发转移概率,使蚂蚁大概率向目标栅格搜索;其次,采用正弦自适应动态调整信息素挥发因子,增强算法的全局搜索能力;最后通过修改路径减少路径冗余,进行路径安全性检查并重新调整路径,减少转弯的次数,从而提高路线质量。通过MATLAB仿真实验表明,改进蚁群算法转弯次数少,规划路径短且安全,搜索时间较快,提高了算法的收敛速度和寻优能力。
Aiming at the problems of large blindness and many inflection points in the early search of traditional ant colony algorithm,the ant colony algorithm was improved as follows.Firstly,in order to enhance the heuristic information of the target position,the distance gain coefficient was introduced to amplify the influence of the target position on the next grid node to be selected.Then the weighted distance heuristic factor was introduced,and the distance heuristic transition probability was added to the state transition probability,so that the ant can search the target grid with high probability.Secondly,the sine adaptive dynamic adjustment pheromone volatilization factor was used to enhance the global search ability of the algorithm.Finally,the path redundancy was reduced by modifying the path,the path safety check was performed and the path was readjusted to reduce the number of turns,thereby improving the route quality.MATLAB simulation experiments show that the improved ant colony algorithm has fewer turns,shorter and safer planning path,faster search time,and improves the convergence speed and optimization ability of the algorithm.
作者
郝兆明
安平娟
李红岩
赵天玥
王磊
杨朝旭
HAO Zhao-ming;AN Ping-juan;LI Hong-yan;ZHAO Tian-yue;WANG Lei;YANG Chao-xu(The college of Electrical and Control Engineering,Xi'an University of Science and Technology,Xi'an 710600,China)
出处
《科学技术与工程》
北大核心
2023年第22期9585-9591,共7页
Science Technology and Engineering
基金
国家自然科学基金(61703329)。
关键词
蚁群算法
状态转移概率
距离启发因子
正弦自适应
ant colony algorithm
state transition probability
distance heuristic factor
sine adaptation
