A Branch and Bound Algorithm for Agile Earth Observation Satellite Scheduling
The agile earth observing satellite scheduling (AEOSS) problem consists of scheduling a subset of images among a set of candidates that satisfy imperative constraints and maximize a gain function. In this paper, we consider a new AEOSS model which integrates a time-dependent temporal constraint. To...
Saved in:
Main Authors: | Xiaogeng Chu, Yuning Chen, Lining Xing |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2017-01-01
|
Series: | Discrete Dynamics in Nature and Society |
Online Access: | http://dx.doi.org/10.1155/2017/7345941 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling
by: He Wang, et al.
Published: (2025-12-01) -
A Dynamic Scheduling Method of Earth-Observing Satellites by Employing Rolling Horizon Strategy
by: Qiu Dishan, et al.
Published: (2013-01-01) -
A Hybrid Genetic Algorithm for Satellite Image Downlink Scheduling Problem
by: Bingyu Song, et al.
Published: (2018-01-01) -
Two-stage deep reinforcement learning method for agile optical satellite scheduling problem
by: Zheng Liu, et al.
Published: (2024-11-01) -
A Satellite Observation Data Transmission Scheduling Algorithm Oriented to Data Topics
by: Hao Chen, et al.
Published: (2020-01-01)