• DocumentCode
    1496878
  • Title

    Constrained Weapon–Target Assignment: Enhanced Very Large Scale Neighborhood Search Algorithm

  • Author

    Lee, Mei-Zi

  • Author_Institution
    Inf. & Commun. Res. Div., Chung-Shan Inst. of Sci. & Technol., Taoyuan, Taiwan
  • Volume
    40
  • Issue
    1
  • fYear
    2010
  • Firstpage
    198
  • Lastpage
    204
  • Abstract
    Optimization problems solved using very large scale neighborhood (VLSN) search algorithms include scheduling problems, the capacitated minimum spanning tree problem, the traveling salesman problem, and weapon-target assignment (WTA). This correspondence paper presents an enhanced VLSN search algorithm for obtaining feasible solutions and constructing improvement graphs. This enhanced VLSN search algorithm solves the constrained WTA (CWTA) problem, in which the number of interceptors available to each weapon and the number of interceptors allowed to fire at each target have upper bounds. The proposed enhanced VLSN search algorithm can solve a CWTA problem with 100 targets and 100 weapons (where the upper bound on the number of interceptors for each weapon is one and both the lower and upper bounds on the number of interceptors for each target are equal to one) within an average of 3 s. This study demonstrates that the proposed Enhanced VLSN is superior to existing approaches.
  • Keywords
    command and control systems; graph theory; optimisation; search problems; travelling salesman problems; capacitated minimum spanning tree problem; constrained weapon-target assignment; large scale neighborhood search algorithm; optimization problems; scheduling problems; traveling salesman problem; weapon-target assignment; Constrained WTA problem; cyclic multiexchange; improvement graph; network flow; valid cycle; very large scale neighborhood (VLSN) search algorithm; weapon–target assignment (WTA);
  • fLanguage
    English
  • Journal_Title
    Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4427
  • Type

    jour

  • DOI
    10.1109/TSMCA.2009.2030163
  • Filename
    5282552