abstract

An approach of satellite periodic continuous observation task scheduling based on evolutionary computation

Authors:

Hao. Chen,

Chun. Du,

Jun. Li,

Ning. Jing,

Lingfeng. WangAuthors Info & Claims

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 15 - 16

https://doi.org/10.1145/3067695.3082033

Published: 15 July 2017 Publication History

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Abstract

The observation task scheduling of Earth Observation Satellites (EOSs) is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that one target only need to be observed once. However, with the development of remote sensing data applications, some new observation requests appear, which need EOSs take image to a target periodically. Considering the characteristic of the problem, a constraint satisfaction problem model with two objective functions is established. Furthermore, a satellite periodic continuous observation task scheduling algorithm based on multiobjective evolutionary algorithm is proposed. Finally, some experiments are implemented to validate correctness and practicability of our algorithm.

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C. Wang, H. Chen, B. Zhai, J. Li, and L. Chen. 2016. Satellite Observing Mission Scheduling Method Based on Case-Based Learning and a Genetic Algorithm. In Proceeding of the 28th International Conference on Tools with Artificial Intelligence. IEEE, San Jose, CA. 2016: 627--634.

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Wang ZBai LLiu XChen YZhao MTao J(2022)Dynamic Task Scheduling in Remote Sensing Data Acquisition from Open-Access Data Using CloudSimApplied Sciences10.3390/app12221150812:22(11508)Online publication date: 12-Nov-2022
https://doi.org/10.3390/app122211508
Fan HYang ZZhang XWu SLong JLiu L(2022)A novel multi-satellite and multi-task scheduling method based on task network graph aggregationExpert Systems with Applications10.1016/j.eswa.2022.117565205(117565)Online publication date: Nov-2022
https://doi.org/10.1016/j.eswa.2022.117565
Kiam JBesada-Portas ESchulte A(2021)Hierarchical Mission Planning with a GA-Optimizer for Unmanned High Altitude Pseudo-SatellitesSensors10.3390/s2105163021:5(1630)Online publication date: 26-Feb-2021
https://doi.org/10.3390/s21051630
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Published In

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2017

1934 pages

ISBN:9781450349390

DOI:10.1145/3067695

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 15 July 2017

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National Natural Science Foundation of China

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SIGEVO

GECCO '17: Genetic and Evolutionary Computation Conference

July 15 - 19, 2017

Berlin, Germany

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Wang ZBai LLiu XChen YZhao MTao J(2022)Dynamic Task Scheduling in Remote Sensing Data Acquisition from Open-Access Data Using CloudSimApplied Sciences10.3390/app12221150812:22(11508)Online publication date: 12-Nov-2022
https://doi.org/10.3390/app122211508
Fan HYang ZZhang XWu SLong JLiu L(2022)A novel multi-satellite and multi-task scheduling method based on task network graph aggregationExpert Systems with Applications10.1016/j.eswa.2022.117565205(117565)Online publication date: Nov-2022
https://doi.org/10.1016/j.eswa.2022.117565
Kiam JBesada-Portas ESchulte A(2021)Hierarchical Mission Planning with a GA-Optimizer for Unmanned High Altitude Pseudo-SatellitesSensors10.3390/s2105163021:5(1630)Online publication date: 26-Feb-2021
https://doi.org/10.3390/s21051630
Wu KZhang DChen ZChen JShao X(2019)Multi-type multi-objective imaging scheduling method based on improved NSGA-III for satellite formation systemAdvances in Space Research10.1016/j.asr.2019.01.006Online publication date: Jan-2019
https://doi.org/10.1016/j.asr.2019.01.006
Long JLi CZhu LChen SLiu J(2018)An Efficient Task Autonomous Planning Method for Small SatellitesInformation10.3390/info90701819:7(181)Online publication date: 20-Jul-2018
https://doi.org/10.3390/info9070181
Li LChen HLi JJing NEmmerich M(2018)Preference-Based Evolutionary Many-Objective Optimization for Agile Satellite Mission PlanningIEEE Access10.1109/ACCESS.2018.28590286(40963-40978)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2859028

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Regional BDS satellite clock estimation with triple-frequency ambiguity resolution based on undifferenced observation

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Regional BDS satellite clock estimation with triple-frequency ambiguity resolution based on undifferenced observation

Application and comparison of hybrid evolutionary multiobjective optimization algorithms for solving task scheduling problem on heterogeneous systems

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