摘要
通过应用在船舶管路优化布局上的迭代更新蚁群算法,对其中所涉及的各参数进行了大量系统的仿真实验,在整个迭代过程中,为了得到动态平衡,自适应调整参数是一个有效的方法,在实验基础上分析了各参数的不同设置对算法性能的影响,以利于蚁群算法的进一步拓展和推广。
Based on the ACO with the iterative pheromone updating for the ship pipe routing design, this paper analyses the influence of the parameters involved in the performance of the algorithm through large numbers of simulation experiments. To obtain a dynamic balance between exploitation and exploration during the evolution, adaptively adjusting parameters with the states of evolution is an effective measure. The results are beneficial to the application and development of the ant colony algorithm in optimization problems.
出处
《计算机工程》
CAS
CSCD
北大核心
2007年第15期36-39,共4页
Computer Engineering
关键词
船舶管路
蚁群优化
参数
标准差
离散度
ship pipe
ant colony optimization（ACO）
parameter
standard deviation
dispersion
