Multi-Objective Optimization for Submarine Cable Route Planning Based on the Ant Colony Optimization Algorithm

被引：5
|
作者：
Zhao, Zanshan [1 ,2 ]
Wang, Jingting [1 ]
Gao, Guanjun [1 ]
Wang, Haoyu [1 ]
Wang, Daobin [3 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing 100876, Peoples R China
[2] Chinese Acad Sci, Inst Acoust, Hainan Acoust Lab, Haikou 570100, Peoples R China
[3] Lanzhou Univ Technol, Sch Sci, Lanzhou 730050, Peoples R China
来源：
PHOTONICS | 2023年 / 10卷 / 08期
基金：
中国国家自然科学基金;
关键词：
submarine cable route planning; multi-objective optimization; ant colony optimization;
D O I：
10.3390/photonics10080896
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
It is essential to design an appropriate submarine cable route to reduce costs and improve reliability. A methodology that can be used for multi-objective optimization in submarine cable route planning is proposed and numerically studied in this paper. The costs and risks are numerically assessed and mapped to the geographical map. The pheromone and heuristic functions of the ant colony optimization (ACO) algorithm are associated with the geographical map of costs and risks, which enables it to search for a submarine cable route with multi-objective optimization. The results show that the submarine cable route designed by the methodology can effectively avoid high-cost and high-risk regions, which means that the designed submarine cable route is cost-effective and highly reliability.
引用
收藏
页数：13
相关论文
共 50 条
  • [1] A multi-objective disassembly planning approach with ant colony optimization algorithm
    Lu, C.
    Huang, H. Z.
    Fuh, J. Y. H.
    Wong, Y. S.
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2008, 222 (11) : 1465 - 1474
  • [2] Urban Projects Planning by Multi-objective Ant Colony Optimization Algorithm
    Khelifa, Boudjemaa
    Laouar, Mohamed Ridda
    ICIST '18: PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES, 2018,
  • [3] Multi-objective optimization for submarine optical cable route planning based on cross reinforcement learning
    Zhao, Zanshan
    Gao, Guanjun
    Gan, Weiming
    Zhang, Jialiang
    Wang, Zengfu
    Wang, Haoyu
    Guo, Yonggang
    JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING, 2024, 16 (10) : 1018 - 1033
  • [4] Improved ant colony algorithm for multi-objective optimization
    2005, Univ. of Electronic Science and Technology of China, Chengdu, China (34):
  • [5] Multi-objective Ant Colony Optimization Algorithm Based on Load Balance
    Zhu, Liwen
    Tang, Ruichun
    Tao, Ye
    Ren, Meiling
    Xue, Lulu
    CLOUD COMPUTING AND SECURITY, ICCCS 2016, PT I, 2016, 10039 : 193 - 205
  • [6] Multi-Objective Optimization of Smart Grid Based on Ant Colony Algorithm
    Shi, Zhongsheng
    Kumar, Rajiv
    Tomar, Ravi
    ELECTRICA, 2022, 22 (03): : 395 - 402
  • [7] Multi-objective Optimization of Reentry Trajectory Planning for Hypersonic Aircraft Based on Ant Colony Algorithm
    Jiao, Xin
    Jiang, Ju
    2014 IEEE CHINESE GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC), 2014, : 1203 - 1208
  • [8] Ant colony optimization for multi-objective optimization problems
    Alaya, Ines
    Solnon, Christine
    Ghedira, Khaled
    19TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, VOL I, PROCEEDINGS, 2007, : 450 - 457
  • [9] Application of ant colony optimization algorithm based on farthest point optimization and multi-objective strategy in robot path planning☆
    Wu, Shuai
    Dong, Ani
    Li, Qingxia
    Wei, Wenhong
    Zhang, Yuhui
    Ye, Zijing
    APPLIED SOFT COMPUTING, 2024, 167
  • [10] Research on multi-objective optimization of Construction Project based on Ant Colony Algorithm
    Tan Fei
    Hu Heng
    CRIOCM2009: INTERNATIONAL SYMPOSIUM ON ADVANCEMENT OF CONSTRUCTION MANAGEMENT AND REAL ESTATE, VOLS 1-6, 2009, : 1900 - 1906
12345