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Research of Resource Selection Algorithm of Parallel Simulation System for Command Decisions Support Driven by Real-Time Intelligence

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Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems (AsiaSim 2016, SCS AutumnSim 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 643))

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Abstract

At present, operational decision to the commanders rely mainly on human judgment. C4ISR system can hardly assist commanders to predict situation as well as formulate and evaluate operational plans because they are lack of effective tools and methods. Parallel simulation provide an effective to solve the above problems. However, the uncertain and incomplete battlefield intelligence in the ‘battlefield fog’ bring great disturbance to construct parallel simulation system. So it’s an urgent problem to be solved to select the most suitable battlefield entity model based on real-time battlefield intelligence in order to increase models reliability and fidelity. In this paper we propose a parallel simulation system resource selection algorithm (PSSRSA). This algorithm adopts an improved particle swarm optimum (PSO). It also has dynamic inertia weight and an alternative method of mutation. The PSSRSA can overcome traditional PSO shortcomings that may easily fall into local optima or have slow convergence rate. Through the experiment we test the algorithm performance. The results indicate the PSSRSA that is feasible and effective in parallel simulation system resource selection.

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Authors and Affiliations

  1. Science and Technology on Information System Engineering Laboratory, CETC 28th, Nanjing, China

    Lin Jianning, Sun Liyang & Mao Shaojie

  2. Nanjing University Posts and Telecommunications, Nanjing, China

    Jiang Jing

Authors
  1. Lin Jianning
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  2. Jiang Jing
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  3. Sun Liyang
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  4. Mao Shaojie
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Corresponding author

Correspondence to Lin Jianning .

Editor information

Editors and Affiliations

  1. Beihang University, Beijing, China

    Lin Zhang

  2. Beihang University, Beijing, China

    Xiao Song

  3. Beihang University, Beijing, China

    Yunjie Wu

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© 2016 Springer Science+Business Media Singapore

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Jianning, L., Jing, J., Liyang, S., Shaojie, M. (2016). Research of Resource Selection Algorithm of Parallel Simulation System for Command Decisions Support Driven by Real-Time Intelligence. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 643. Springer, Singapore. https://doi.org/10.1007/978-981-10-2663-8_44

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  • DOI: https://doi.org/10.1007/978-981-10-2663-8_44

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2662-1

  • Online ISBN: 978-981-10-2663-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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