Paper Info
Title
A Population Perturbation And Elimination Strategy Based Genetic Algorithm For Multi-Satellite Tt&C Scheduling Problem
Abstract
The Multi-satellite Tracking Telemetry and Command (TT&C) Scheduling, a multi-constrained and high-conflict complex combinatorial optimization problem, is a typical NP-hard problem. The effective utilization of existing TT&C resources has always played a key role in the satellite field. This paper first simplified the problem and established a corresponding mathematical model with the hybrid objective of maximizing the profit and task completion rate. Considering the significant effect of genetic algorithm in solving the problem of resource allocation, a population perturbation and elimination strategy based genetic algorithm (GA-PE) which focused on the Multi-Satellite TT&C Scheduling problem was proposed. For each case, a task scheduling sequence was first obtained through the GA-PE algorithm, and then a task planning algorithm will be used to determine which tasks can be scheduled. Compared with several efficient heuristic algorithms, a series of computational experiments have illustrated its better performance in both profit and task completion rates. The experiments of strategy and parameter sensitivity verification have investigated the performance of GA-PE in various aspects thoroughly.
Year
DOI
Venue
2021
10.1016/j.swevo.2021.100912
SWARM AND EVOLUTIONARY COMPUTATION
Keywords
DocType
Volume
Genetic algorithm, Multi-satellite TT&C scheduling, intelligent optimization method, Bio-inspired computing
Journal
65
ISSN
Citations 
PageRank 
2210-6502
1
0.35
References 
Authors
0
5
Name
Order
Citations
PageRank
Chen Ming11211.07
Jun Wen210.35
Yan-Jie Song320.71
Lining Xing4168.51
Ying-Wu Chen510.35