Weapon Target Assignment Based on Improved Fireworks Algorithm

Yaohong Qu, Wenlong Wang, Kai Wang, Qingyu Du

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Aiming at the complex multi-constraint weapon target assignment problem, an improved fireworks algorithm is proposed in this paper, which introduces reverse learning strategy to the traditional method. The reverse learning strategy enables the algorithm to have greater exploration and mining ability. Simulation results show that the proposed algorithm has faster calculation speed and stronger robust capability to avoid falling into the local convergence than the conventional ones.

Original languageEnglish
Title of host publicationAdvances in Guidance, Navigation and Control - Proceedings of 2020 International Conference on Guidance, Navigation and Control, ICGNC 2020
EditorsLiang Yan, Haibin Duan, Xiang Yu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages2587-2597
Number of pages11
ISBN (Print)9789811581540
DOIs
StatePublished - 2022
EventInternational Conference on Guidance, Navigation and Control, ICGNC 2020 - Tianjin, China
Duration: 23 Oct 202025 Oct 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume644 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Guidance, Navigation and Control, ICGNC 2020
Country/TerritoryChina
CityTianjin
Period23/10/2025/10/20

Keywords

  • Fireworks algorithm
  • Multiple objective optimization
  • Weapon target assignment

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