首页|Multi-group ant colony algorithm based on simulated annealing method
Multi-group ant colony algorithm based on simulated annealing method
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
万方数据
To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulated annealing method is introduced to the algorithm. Through setting the temperature changing with the iterations, after each turn of tours, the solution set obtained by the ants is taken as the candidate set. The update set is obtained by adding the solutions in the candidate set to the previous update set with the probability determined by the temperature. The solutions in the candidate set are used to update the trail information. In each turn of updating, the current best solution is also used to enhance the tail information on the current best route. The tail information is reset when the algorithm is in stagnation state. The computer experiments demonstrate that the proposed algorithm has higher stability and convergence speed.
ant colony algorithmsimulated annealing methodmulti-groupcandidate setupdate set
ZHU Jing-wei、RUI Ting、LIAO Ming、ZHANG Jin-lin
展开 >
Engineering Institute of Engineering Corps, People's Liberation Army University of Science and Technology, Nanjing 210007, P. R. China
NETL
NSTL
万方数据
