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DOI: 10.14569/IJARAI.2013.020707
PDF

Weapon Target Assignment with Combinatorial Optimization Techniques

Author 1: Asim Tokgöz
Author 2: Serol Bulkan

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 2 Issue 7, 2013.

  • Abstract and Keywords
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Abstract: Weapon Target Assignment (WTA) is the assignment of friendly weapons to the hostile targets in order to protect friendly assets or destroy the hostile targets and considered as a NP-complete problem. Thus, it is very hard to solve it for real time or near-real time operational needs. In this study, genetic algorithm (GA), tabu search (TS), simulated annealing (SA) and Variable Neighborhood Search (VNS) combinatorial optimization techniques are applied to the WTA problem and their results are compared with each other and also with the optimized GAMS solutions. Algorithms are tested on the large scale problem instances. It is found that all the algorithms effectively converge to the near global optimum point(s) (a good quality) and the efficiency of the solutions (speed of solution) might be improved according to the operational needs. VNS and SA solution qualities are better than both GA and TS.

Keywords: Weapon Target Assignment; Combinatorial Optimization; Genetic Algorithm; Tabu Search; Simulated Annealing; Variable Neighborhood Search; WTA; WASA; TEWASA

Asim Tokgöz and Serol Bulkan, “Weapon Target Assignment with Combinatorial Optimization Techniques” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 2(7), 2013. http://dx.doi.org/10.14569/IJARAI.2013.020707

@article{Tokgöz2013,
title = {Weapon Target Assignment with Combinatorial Optimization Techniques},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2013.020707},
url = {http://dx.doi.org/10.14569/IJARAI.2013.020707},
year = {2013},
publisher = {The Science and Information Organization},
volume = {2},
number = {7},
author = {Asim Tokgöz and Serol Bulkan}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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