A distance similarity-based genetic optimization algorithm for satellite ground network planning considering feeding mode

作     者：Ren, Yingying Li, Qiuli Guo, Yangyang Pedrycz, Witold Xing, Lining Liu, Anfeng Song, Yanjie 

作者机构：Guangxi Univ Sch Comp Elect & Informat Nannig Peoples R China Network Technol Guangxi Key Lab Multimedia Commun Nanning Peoples R China Guangxi Univ Key Lab Parallel Distributed & Intelligent Comp Nanning Peoples R China Beijing Jiaotong Univ Sch Syst Sci Beijing Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB Canada Polish Acad Sci Syst Res Inst Warsaw Poland Fac Engn & Nat Sci Dept Comp Engn Istanbul Turkiye Xidian Univ Sch Elect Engn Xian Peoples R China Cent South Univ Sch Elect Engn Changsha Peoples R China Dalian Maritime Univ Natl Engn Res Ctr Maritime Nav Syst Dalian Peoples R China 

出 版 物：《EXPERT SYSTEMS WITH APPLICATIONS》 (Expert Sys Appl)

年 卷 期：2025年第268卷

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China [723B2002] Guangxi Intelligent Digital Services Research Center of Engineering Technology, China Key Laboratory of Parallel, Distributed and Intelligent Computing (Guangxi University), China, Education Department of Guangxi Zhuang Autonomous Region Open Subject, China Natural Science Foundation of Guangxi, China Guangxi Natural Science Foundation, China [2024JJB170042] 62072124 IDSOP2305 2023JJG170006 

主　　题：Communications satellite Satellite ground networking Feed-switching Similarity assessment Evolutionary algorithms 

摘      要：With the rapid development of the satellite industry, the information transmission network based on communication satellites has gradually become a major and important part of the future satellite ground integration network. However, the low transmission efficiency of the satellite data relay back mission has become a problem that is currently constraining the construction of the system and needs to be solved urgently. Effectively planning the task of satellite ground networking by reasonably scheduling resources is crucial for the efficient transmission of task data. In this paper, we hope to provide a task execution scheme that maximizes the profit of the networking task for satellite ground network planning considering feeding mode (SGNPFM). To solve the SGNPFM problem, a mixed-integer planning model with the objective of maximizing the gain of the link-building task is constructed, which considers various constraints of the satellite in the feed-switching mode. Based on the problem characteristics, we propose a distance similarity-based genetic optimization algorithm (DSGA), which considers the state characteristics between the tasks and introduces a weighted Euclidean distance method to determine the similarity between the tasks. To obtain more high-quality solutions, different similarity evaluation methods are designed to assist the algorithm in intelligently screening individuals. The DSGA also uses an adaptive crossover strategy based on similarity mechanism, which guides the algorithm to achieve efficient population search. In addition, a task scheduling algorithm considering the feed-switching mode is designed for decoding the algorithm to generate a high-quality scheme. The results of simulation experiments show that the DSGA can effectively solve the SGNPFM problem. Compared to other algorithms, the proposed algorithm not only obtains higher quality planning schemes but also has faster algorithm convergence speed. The proposed algorithm improves data tra