Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation
With the development of aerospace science and technology, Earth Observation Satellite cluster which consists of heterogeneous satellites with many kinds of payloads appears gradually. Compared with the traditional satellite systems, satellite cluster has some particular characteristics, such as larg...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2018/2103625 |
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doaj-004e1ab1343747afbe0a0e693c25b4002020-11-24T22:40:02ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472018-01-01201810.1155/2018/21036252103625Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team FormationHao Chen0Shu Yang1Jun Li2Ning Jing3College of Electronic Science, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science, National University of Defense Technology, Changsha 410073, ChinaWith the development of aerospace science and technology, Earth Observation Satellite cluster which consists of heterogeneous satellites with many kinds of payloads appears gradually. Compared with the traditional satellite systems, satellite cluster has some particular characteristics, such as large-scale, heterogeneous satellite platforms, various payloads, and the capacity of performing all the observation tasks. How to select a subset from satellite cluster to perform all observation tasks effectively with low cost is a new challenge arousing in the field of aerospace resource scheduling. This is the agent team formation problem for observation task-oriented satellite cluster. A mathematical scheduling model is built. Three novel algorithms, i.e., complete search algorithm, heuristic search algorithm, and swarm intelligence optimization algorithm, are proposed to solve the problem in different scales. Finally, some experiments are conducted to validate the effectiveness and practicability of our algorithms.http://dx.doi.org/10.1155/2018/2103625 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hao Chen Shu Yang Jun Li Ning Jing |
spellingShingle |
Hao Chen Shu Yang Jun Li Ning Jing Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation Mathematical Problems in Engineering |
author_facet |
Hao Chen Shu Yang Jun Li Ning Jing |
author_sort |
Hao Chen |
title |
Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation |
title_short |
Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation |
title_full |
Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation |
title_fullStr |
Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation |
title_full_unstemmed |
Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation |
title_sort |
exact and heuristic methods for observing task-oriented satellite cluster agent team formation |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2018-01-01 |
description |
With the development of aerospace science and technology, Earth Observation Satellite cluster which consists of heterogeneous satellites with many kinds of payloads appears gradually. Compared with the traditional satellite systems, satellite cluster has some particular characteristics, such as large-scale, heterogeneous satellite platforms, various payloads, and the capacity of performing all the observation tasks. How to select a subset from satellite cluster to perform all observation tasks effectively with low cost is a new challenge arousing in the field of aerospace resource scheduling. This is the agent team formation problem for observation task-oriented satellite cluster. A mathematical scheduling model is built. Three novel algorithms, i.e., complete search algorithm, heuristic search algorithm, and swarm intelligence optimization algorithm, are proposed to solve the problem in different scales. Finally, some experiments are conducted to validate the effectiveness and practicability of our algorithms. |
url |
http://dx.doi.org/10.1155/2018/2103625 |
work_keys_str_mv |
AT haochen exactandheuristicmethodsforobservingtaskorientedsatelliteclusteragentteamformation AT shuyang exactandheuristicmethodsforobservingtaskorientedsatelliteclusteragentteamformation AT junli exactandheuristicmethodsforobservingtaskorientedsatelliteclusteragentteamformation AT ningjing exactandheuristicmethodsforobservingtaskorientedsatelliteclusteragentteamformation |
_version_ |
1725706217157820416 |