Solving the Observing and Downloading Integrated Scheduling Problem of Earth Observation Satellite with a Quantum Genetic Algorithm

Zhang Ye (), Hu Xiaoxuan (), Zhu Waiming () and Jin Peng ()
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Zhang Ye: School of Management, Hefei University of Technology, Hefei230009, China
Hu Xiaoxuan: School of Management, Hefei University of Technology, Hefei230009, China
Zhu Waiming: School of Management, Hefei University of Technology, Hefei230009, China
Jin Peng: School of Management, Hefei University of Technology, Hefei230009, China

Journal of Systems Science and Information, 2018, vol. 6, issue 5, 399-420

Abstract: This paper addresses the integrated Earth observation satellite scheduling problem. It is a complicated problem because observing and downloading operations are both involved. We use an acyclic directed graph model to describe the observing and downloading integrated scheduling problem. Based on the model which considering energy constraints and storage capacity constraints, we develop an efficient solving method using a novel quantum genetic algorithm. We design a new encoding and decoding scheme that can generate feasible solution and increase the diversity of the population. The results of the simulation experiments show that the proposed method solves the integrated Earth observation satellite scheduling problem with good performance and outperforms the genetic algorithm and greedy algorithm on all instances.

Keywords: Earth observation satellite; integrated scheduling; quantum genetic algorithm (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:6:y:2018:i:5:p:399-420:n:2

DOI: 10.21078/JSSI-2018-399-22

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