Three multi-objective memetic algorithms for observation scheduling problem of active-imaging agile earth observation satellites

Observation scheduling problem for agile earth observation satellites (OSPFAS) plays a critical role in management of agile earth observation satellites (AEOSs). Active imaging enriches the extension of OSPFAS, we call the novel problem as observation scheduling problem for AEOS with variable image...

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Vydáno v:Annals of operations research Ročník 346; číslo 2; s. 861 - 893
Hlavní autoři: Chang, Zhongxiang, Zhou, Zhongbao
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.03.2025
Springer Nature B.V
Témata:
Active satellites
Algorithms
Business and Management
Combinatorics
Energy consumption
Experiments
Genetic algorithms
Heuristic
Image quality
Knowledge
Multiple objective analysis
Operations research
Operations Research/Decision Theory
Operators
Optimization
Optimization models
Original - OR Modeling/Case Study
Satellite imagery
Satellite observation
Scheduling
Simulation
Theory of Computation
Memetic computing
Scheduling
Multi-objective optimization
Active imaging
Cumulative image quality
OSWVID
ISSN:0254-5330, 1572-9338
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Shrnutí:Observation scheduling problem for agile earth observation satellites (OSPFAS) plays a critical role in management of agile earth observation satellites (AEOSs). Active imaging enriches the extension of OSPFAS, we call the novel problem as observation scheduling problem for AEOS with variable image duration (OSWVID). A cumulative image quality and a detailed energy consumption is proposed to build OSWVID as a bi-objective optimization model. Three multi-objective memetic algorithms, PD+NSGA-II, LA+NSGA-II and ALNS+NSGA-II, are then designed to solve OSWVID. Considering the heuristic knowledge summarized in our previous research, several operators are designed for improving these three algorithms respectively. Based on existing instances, we analyze the critical optimization parameters, evolution operators, and efficiency of these three algorithms based on extensive simulation experiments.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-024-06156-5