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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