Large-Scale Weapon Target Assignment Based on Improved MOEA/D Algorithm

Huiyang Yu, Tao Xu, Xiaoguang Wang, Xiaojian Yi*, Junnan Chen

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

In this paper, a modified MOEA/D algorithm with wider spread of solutions and faster convergence rate is developed to solve the static weapon target assignment problem. First, a bi-objective static weapon target assignment model is proposed for large-scale heterogeneous missile clusters and large- scale multi type targets assignment. Second, a decimal encoding method is designed to discribe multi-type weapons, where the population is updated by using the crossover and mutation operators and a repair operator is designed to rectify new generation. Third, the normalized Tchebycheff approach is adpoted to solve the problem of the difference of bi-objective scale. Finally, the advantage of the modified algorithm is illustrated by some numerical experiments.

Original languageEnglish
Title of host publication2022 4th International Conference on System Reliability and Safety Engineering, SRSE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages86-91
Number of pages6
ISBN (Electronic)9781665473880
DOIs
Publication statusPublished - 2022
Event4th International Conference on System Reliability and Safety Engineering, SRSE 2022 - Guangzhou, China
Duration: 15 Dec 202218 Dec 2022

Publication series

Name2022 4th International Conference on System Reliability and Safety Engineering, SRSE 2022

Conference

Conference4th International Conference on System Reliability and Safety Engineering, SRSE 2022
Country/TerritoryChina
CityGuangzhou
Period15/12/2218/12/22

Keywords

  • MOEA/D
  • NSGA-II
  • ideal-nadir Tchebycheff approach
  • weapon target assignment

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