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Improved WTA problem solving method using a parallel genetic algorithm which applied the RMI initialization method

Authors
Hong, S.-S.Yun, J.Choi, B.Kong, J.Han, M.-M.
Issue Date
2012
Keywords
Genetic Algorithm; Optimization; Parallel Process; Population Intialization; Weapon Assignment
Citation
6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012, pp.2189 - 2193
Journal Title
6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
Start Page
2189
End Page
2193
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17514
DOI
10.1109/SCIS-ISIS.2012.6505315
ISSN
0000-0000
Abstract
The problem of Weapon Target Allocation (WTA) is to find an optimum solution, the type of vector that our weapons assign to targets, to minimize the damage of our assets from the target of an enemy offending us. we proposed the novel parallel genetic algorithm for solved to the WTA problem. The proposed. As the first step, our proposed algorithm is to expand the problem search space through the Random Mutation Inherit (RMI) population initialization method thereby improving convergence performance. We proposed an algorithm which obtains the WTA solution quickly and solves the WTA problem efficiently. © 2012 IEEE.
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