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On Relaxing and Steady State Genetic Methods for Satellite Imaging Scheduling
August 06-August 08
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SNPD.2008.1082008 Ninth ACIS International Confere ...
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Jin Xiao-shan, Li Jun, Jing Ning, "On Relaxing and Steady State Genetic Methods for Satellite Imaging Scheduling," Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on, pp. 141-146, 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2008.
 
 
BibTex
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@article{ 10.1109/SNPD.2008.108,
author = {Jin Xiao-shan and Li Jun and Jing Ning},
title = {On Relaxing and Steady State Genetic Methods for Satellite Imaging Scheduling},
journal ={Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on},
volume = {0},
year = {2008},
isbn = {978-0-7695-3263-9},
pages = {141-146},
doi = {http://doi.ieeecomputersociety.org/10.1109/SNPD.2008.108},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
TI - On Relaxing and Steady State Genetic Methods for Satellite Imaging Scheduling
SN - 978-0-7695-3263-9
SP141
EP146
A1 - Jin Xiao-shan,
A1 - Li Jun,
A1 - Jing Ning,
PY - 2008
KW - null
VL - 0
JA - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
ER -
 
Satellite imaging scheduling problem with energy and memory limit belongs to NP-Hard problems. As the mathematical programming model is built, a Lagrangian relaxation method can provide tight upper bound, using a max-weighted path algorithm in the constraint graph and a sub-gradient optimizing method to explore the minimum upper bound. Then, Permutation based stochastic local search algorithms are used to optimize imaging scheduling results. Finally, the testing results demonstrate the efficiency of these methods.
Citation:
Jin Xiao-shan, Li Jun, Jing Ning, "On Relaxing and Steady State Genetic Methods for Satellite Imaging Scheduling," snpd, pp.141-146, 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2008
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