计算机应用与软件2018，Vol.35Issue(2)：261-266,6.DOI:10.3969/j.issn.1000-386x.2018.02.047
求解TSP问题的自适应模拟退火蚁群算法
ADAPTIVE SIMULATED ANNEALING ANT COLONY ALGORITHM FOR SOLVING TSP PROBLEM
摘要
Abstract
Aiming at the problem that the ant colony algorithm is easy to fall into the local optimum and the convergence speed is slow,an adaptive simulated annealing ant colony algorithm was proposed based on the maximum -minimum ant colony algorithm.The algorithm accepted the difference solution with a certain probability at a high temperature.The path was optimized after each iteration.The global search ability of the algorithm was increased,and an adaptive pheromone updating strategy was adopted.The global search ability of the algorithm was increased in the early stage and accelerated the convergence speed of the algorithm in the later stage.In the low temperature stage, the speed of the algorithm was accelerated by the value of the temperature coefficient, and then the tempering mechanism was adopted to avoid the local optimum.The quality of the solution was improved.At the same time,the 3opt algorithm was used to further optimize the quality of the algorithm.The experimental results showed that the convergence speed and the solution quality of the proposed algorithm had been improved to a certain extent,and it could balance the relationship between population diversity and convergence rate.关键词
最大-最小蚁群算法/模拟退火算法/自适应信息素更新/旅行商问题Key words
Max-min ant system/Simulated annealing algorithm/Adaptive pheromone update/Traveling salesman problem分类
信息技术与安全科学引用本文复制引用
袁汪凰,游晓明,刘升,朱艳..求解TSP问题的自适应模拟退火蚁群算法[J].计算机应用与软件,2018,35(2):261-266,6.基金项目
国家自然科学基金项目(61673258,61075115). （61673258,61075115）
