Title: A hierarchical parallel evolutionary algorithm of distributed and multi-threaded two-level structure for multi-satellite task planning

Authors: Man Zhao; Dongcheng Li

Addresses: Key Laboratory of Geological Survey and Evaluation of Ministry of Education, School of Computer, China University of Geosciences, 388 Lumo Road, Wuhan, 430074, China ' Department of Computer Science, University of Texas at Dallas, Richardson, TX, 75080, USA

Abstract: The aim of multi-satellite task planning is to study how to distribute limited resources of satellites and payloads and execution time for observation missions to be completed within a limited set of available satellites so as to best satisfy the observational demand. Aiming at the shortcomings of the current study on multi-satellite task planning, this paper proposes a hierarchical parallel evolution algorithm framework which is based on a distributed and multi-threaded two-level structure. It adopts parallel communication flow and task distribution strategy of multi-machine, multi-core and two-level structure. The distributed parallel evolution model work among multi-machines, whereas the multi-threaded parallel evolution model work among multi-cores to reduce the communication overhead of the parallel system while maintaining the global optimisation of the algorithm. The result of the experiment showed that the multi-satellite task planning evolutionary optimisation model established in the paper is effective. Subsequently, it was proven that the hierarchical parallel-evolving algorithm proposed by the paper can greatly cut down the time consumed for the evolution and improve the algorithm solving efficiency, which can effectively solve both the multi-satellite task planning issue and optimisation problems in other fields. It is thus of important use value.

Keywords: multi-satellite task planning; distributed; multi-threading; parallel computing; differential-evolution algorithm.

DOI: 10.1504/IJAAC.2020.110075

International Journal of Automation and Control, 2020 Vol.14 No.5/6, pp.612 - 633

Received: 22 Dec 2018
Accepted: 03 Jul 2019

Published online: 05 Oct 2020 *

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