A real adjacency matrix-coded evolution algorithm for highly linkage-based routing problems
A real adjacency matrix-coded evolution algorithm for highly linkage-based routing problems
复制标题
一种针对高度链接路由问题的真实邻接矩阵编码演化算法
DOI：
10.1504/ijbic.2021.117426
复制
发表时间：
2021
影响因子：
3.5
通讯作者：
Li Gang
中科院分区：
文献类型：
--
作者：
Wei Hang;Huang Han（通讯）;Hao Zhi-Feng;Chen Qin-Qun;Witold Pedrycz;Li Gang
In routing problems, the contribution of a variable to fitness often depends on the .states of other variables. This phenomenon is referred to as linkage. High linkage level typically .makes a routing problem more challenging for an evolutionary algorithm (EA). An entire linkage .measure, named entire linkage index (ELI), has been proposed in this paper for such routing .problems. Aiming at solving high linkage-based routing problems, we presented a real adjacency .matrix-coded evolution algorithm (RAMEA) that is capable of learning and evolving correlation .matrix of decision variables. The efficiency of RAMEA was tested on two familiar routing .problems: travelling salesman problem (TSP) and generalised travelling salesman problem .(GTSP). The experimental results show that the RAMEA is promising for those highly .linkage-based routing problems, especially for those of large-scale.
