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Neural Processing Letters

, Volume 50, Issue 3, pp 3045–3057 | Cite as

Projection Recurrent Neural Network Model: A New Strategy to Solve Weapon-Target Assignment Problem

  • Alireza Shojaeifard
  • Ali Nakhaei Amroudi
  • Amin MansooriEmail author
  • Majid Erfanian
Article
  • 55 Downloads

Abstract

In the present research, we are going to obtain the solution of the Weapon-Target Assignment (WTA) problem. According to our search in the scientific reported papers, this is the first scientific attempt for resolving of WTA problem by projection recurrent neural network (RNN) models. Here, by reformulating the original problem to an unconstrained problem a projection RNN model as a high-performance tool to provide the solution of the problem is proposed. In continuous, the global exponential stability of the system was proved in this research. In the final step, some numerical examples are presented to depict the performance and the feasibility of the method. Reported results were compared with some other published papers.

Keywords

Weapon-target assignment problem Nonlinear optimization problem Projection recurrent neural network Global exponential stability Projection function 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsImam Hossein Comprehensive UniversityTehranIran
  2. 2.Department of Applied MathematicsFerdowsi University of MashhadMashhadIran
  3. 3.Department of Science, School of Mathematical SciencesUniversity of ZabolZabolIran

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