Weapon target assignment leveraging strong submodularity

Zengfu Wang, Xuezhi Wang, Yan Liang, Quan Pan

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

7 Scopus citations

Abstract

Optimal weapon target assignment problem involves NP-complete searching process and becomes computationally impractical as the number of weapons and targets increases. Existing approaches, therefore, only consider approximate method with heuristic searching scenarios, which are, however, no theoretical performance guarantee for the level of accuracy that the underlying algorithm may achieve. In this paper, the weapon target assignment problem is studied in the framework of combinatorial optimization theory. Following a previous work, an accelerated continuous greedy algorithm is proposed to address the underlying problem in polynomial time. The algorithm is proved to have the best guaranteed performance against optimal solution among the existing polynomial time methods.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Information and Automation, ICIA 2013
Pages74-79
Number of pages6
DOIs
StatePublished - 2013
Event2013 IEEE International Conference on Information and Automation, ICIA 2013 - Yinchuan, China
Duration: 26 Aug 201328 Aug 2013

Publication series

Name2013 IEEE International Conference on Information and Automation, ICIA 2013

Conference

Conference2013 IEEE International Conference on Information and Automation, ICIA 2013
Country/TerritoryChina
CityYinchuan
Period26/08/1328/08/13

Keywords

  • Heuristics
  • Submodularity
  • Weapon Target Assignment

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