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
Link To Document :
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