ZHOU Hao-li, LI Tai-jun, XIAO Sha, et al. Optimization for bidirectional ant colony algorithm based on microcanonical annealing[J]. 2016, 35(4): 127-129+133.
ZHOU Hao-li, LI Tai-jun, XIAO Sha, et al. Optimization for bidirectional ant colony algorithm based on microcanonical annealing[J]. 2016, 35(4): 127-129+133. DOI: 10.13873/J.1000-9787(2016)04-0127-03.
微正则退火的双向蚁群优化算法
摘要
双向蚁群搜索算法可以提高算法的搜索速度
并可以选择搜索的空间;微正则退火算法具有准确度高、速度快等优点
可以实现全局路径优化搜索。结合两种算法的优点
提出了双向蚁群微正则退火算法
用来求解海量数据网络下的旅行商问题。通过实验表明:双向蚁群微正则退火算法不容易陷入局部最优解
且在寻找全局最优解和运行效率上都比其他算法更有优势。
Abstract
Bidirectional ant colony search algorithm can improve search speed and select search space;microcanonical annealing algorithm can realize global path optimization search with high speed and accuracy.Combine advantages of the two algorithms and propose bi-ACO microcanonical annealing algorithm for solving traveling salesman problem in massive data network. Experiments show that bi-ACO microcanonical annealing algorithm is not easy to fall into local optimal solution
and it has more advantages in searching for globally optimal solution and operating efficiency than other algorithms.