@Article{JICS-18-67,
author = {Dong , PingxianGuo , FangChen , ChenSong , XiaofanWang , HuiBai , PingpingQi , HuanruoQian , YimingZhang , Haojie and Han , Yunhao},
title = {Cable Laying Path Planning Based on Optimized Ant Colony Algorithm},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {18},
number = {1},
pages = {67--80},
abstract = {<p style="text-align: justify;">To address the large error and low efficiency of traditional manual design in
cable laying task, the computer-aided design optimized by Ant Colony Algorithm (ACA)
is applied to cable laying path planning. The shortest path for cable laying is solved via
the ACA&#39;s multi terminal path calculation for complex path planning. Furthermore, the
planarized cable laying path is optimized via Gompertz function in aspects of
pheromone restriction and self-adaptive adjustment of volatilization factor, thus
improves the ACA in both convergence speed and global performance. The simulation
results show that the optimized ant colony algorithm can quickly obtain the shortest
cable laying path in the task of substation digital 3D cable laying, which saves the cost
of manpower and materials, and improves the design accuracy.</p>},
issn = {1746-7659},
doi = {https://doi.org/10.4208/JICS-2023-005},
url = {http://global-sci.org/intro/article_detail/jics/23721.html}
}