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基于多目标进化算法的侦察星座优化方法研究

刘亚丽 熊伟

指挥控制与仿真2024,Vol.46Issue(4):97-104,8.
指挥控制与仿真2024,Vol.46Issue(4):97-104,8.DOI:10.3969/j.issn.1673-3819.2024.04.013

基于多目标进化算法的侦察星座优化方法研究

Research on optimization method of reconnaissance constellation based on multi-objective evolutionary algorithm

刘亚丽 1熊伟1

作者信息

  • 1. 航天工程大学复杂电子系统仿真实验室,北京 101416
  • 折叠

摘要

Abstract

In order to further solve the optimization problem of reconnaissance constellation and strengthen the construction of space-based reconnaissance system,the current optimization methods of reconnaissance constellation are studied and sum-marized.The design and optimization of reconnaissance constellation has the characteristics of multi-parameter,multi-objec-tive,nonlinear and discontinuous,which is a typical multi-objective optimization problem.Multi-objective evolutionary algo-rithm is a kind of biological intelligence algorithm based on population,which carries out probabilistic search in decision space according to predetermined heuristic rules.It does not need continuity,differentiability and other conditions of the problem,and can get a group of solution sets close to Pareto frontier within a limited number of search times.It can effective-ly solve the multi-objective optimization problem and has been widely used in the multi-objective optimization of reconnais-sance constellation.This paper discusses the construction of the reconnaissance constellation optimization model and the clas-sification,advantages and disadvantages of the multi-objective evolutionary algorithm,discusses the application of the multi-objective evolutionary algorithm in the reconnaissance constellation optimization,and points out the development direction of the reconnaissance constellation optimization based on the multi-objective evolutionary algorithm.

关键词

星座优化/天基侦察/进化算法/多目标优化/高维多目标优化

Key words

constellation optimization/space-based reconnaissance/evolutionary algorithm/multi-objective optimization/many-objective optimization

分类

航空航天

引用本文复制引用

刘亚丽,熊伟..基于多目标进化算法的侦察星座优化方法研究[J].指挥控制与仿真,2024,46(4):97-104,8.

基金项目

复杂电子系统仿真实验室基金资助项目(6142401003022109) (6142401003022109)

指挥控制与仿真

OACSTPCD

1673-3819

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