系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (9): 2535-2543.doi: 10.12305/j.issn.1001-506X.2021.09.21

• 系统工程 • 上一篇    下一篇

基于改进遗传算法的多类测控资源调度方法

薛乃阳1,2, 丁丹1,*, 王红敏1, 刘步花2   

  1. 1. 航天工程大学电子与光学工程系, 北京 101416
    2. 航天工程大学研究生院, 北京 101416
  • 收稿日期:2020-10-26 出版日期:2021-08-20 发布日期:2021-08-26
  • 通讯作者: 丁丹
  • 作者简介:薛乃阳(1997—), 男, 硕士研究生, 主要研究方向为航天测控|丁丹(1980—), 男, 副研究员, 博士, 主要研究方向为航天测控|王红敏(1991—), 女, 实习研究员, 硕士, 主要研究方向为航天测控|刘步花(1994—), 女, 硕士研究生, 主要研究方向为航天测控
  • 基金资助:
    军队级项目资助课题

Multi-type TT&C resource scheduling method based on improved genetic algorithm

Naiyang XUE1,2, Dan DING1,*, Hongmin WANG1, Buhua LIU2   

  1. 1. Department of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, China
    2. Graduate School, Space Engineering University, Beijing 101416, China
  • Received:2020-10-26 Online:2021-08-20 Published:2021-08-26
  • Contact: Dan DING
  • Supported by:
    军队级项目资助课题

摘要:

为了研究一类利用不同测控(telemetry, track and command, TT&C)网联合执行TT&C任务的多类TT&C资源联合调度问题, 首先对国有和商业TT&C网的不同特点进行归纳总结。其次,对问题中的约束条件进行分析和规范化描述, 并在满足所选约束的前提下, 建立问题的数学模型。进而根据问题特点, 以遗传算法为基础, 通过设计适当的编码方法和交叉、变异算子以及约束冲突处理方法, 提出一种改进遗传算法。最后,实例仿真表明, 引入的多类TT&C资源联合调度方法较传统未引入联合调度的方法能有效提高TT&C资源利用效率, 证明了所提算法求解此类TT&C调度问题具有较好的性能。

关键词: 航天测控, 多类测控资源联合调度, 改进遗传算法, 调度收益

Abstract:

In order to study the joint scheduling problem of multi class TT & C(telemetry, track and command) resources using different TT & C networks to jointly perform TT & C tasks, the different characteristics of state-owned and commercial TT & C networks are summarized. Secondly, the constraint conditions in the problem are analyzed and described, and the mathematical model of the problem is established on the premise of satisfying the selected constraints. Then, according to the characteristics of the problem, based on genetic algorithm, an improved genetic algorithm is proposed by designing appropriate coding methods, crossover and mutation operators and constraint conflict handling methods. Finally, the simulation results show that the proposed method can effectively improve the utilization efficiency of TT & C resources compared with the traditional method without joint scheduling, which proves that the proposed algorithm has better performance in solving this kind of TT & C scheduling problem.

Key words: aerospace telemetry, track and command (TT&C), joint scheduling of multiple TT&C resources scheduling, improved genetic algorithm, scheduling revenue

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