计算机应用研究2025，Vol.42Issue(6)：1719-1726,8.DOI:10.19734/j.issn.1001-3695.2024.11.0444
基于信息素矩阵优化蚁群算法求解城市建模的旅行商问题
Travelling salesman of urban modeling based on pheromone matrix optimization ant colony algorithm
摘要
Abstract
This paper proposed an optimized ant colony algorithm to address the traveling salesman problem(TSP)in urban modeling.The algorithm integrated random averaging of the pheromone matrix,adaptive perturbation,and dynamic proportional resetting strategies to optimize the path search in the process of acquiring urban modeling materials.After each round of path selection,the algorithm globally updated the local pheromone based on the quality of the paths and accelerated convergence through 2-opt optimization.Initially,it applied the random averaging strategy.When the optimal path had not been updated for multiple iterations,the pheromone of random nodes was averaged to avoid local optima.When multiple attempts at the ran-dom averaging strategy prove ineffective,it introduced the adaptive perturbation strategy.This strategy perturbed the phero-mone matrix to select paths,thereby reducing the risk of local optima.This strategy perturbed the pheromone matrix to select paths,reducing the risk of local optima.When the quality of the optimal path decreases by a certain proportion,it used the dynamic proportional resetting strategy to increase the difference between high and low pheromone values in the matrix,further accelerating convergence.The results show that the algorithm effectively improves global search capability,accelerates the convergence process,and provides a solution to the TSP in urban modeling.关键词
蚁群算法/旅行商问题/组合优化/2-opt算法/城市三维建模Key words
ant colony algorithm/traveler's salesman problem/combinatorial optimization/2-opt algorithm/urban 3D modeling分类
计算机与自动化引用本文复制引用
刘岱,张亚鸣,王凯,崔海青..基于信息素矩阵优化蚁群算法求解城市建模的旅行商问题[J].计算机应用研究,2025,42(6):1719-1726,8.基金项目
中央高校基本科研业务费资助项目(3122025079) （3122025079）
