The modeling and solution of course of action generation based on IN-DEA

The course of action (COA) generation is the course of designing the task planning flow, which is one of the key supporting techniques while the military organization executing aerial operation. Due to the outstanding advantage of influence nets (IN), describing the causal logic between random varia...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 887; no. 1; pp. 12088 - 12096
Main Authors Wan, Lujun, Li, Wen, Dai, Jiangbin, Huang, Aqian
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.08.2017
Subjects
Evolutionary algorithms
Evolutionary computation
Modelling
Physics
Random variables
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Summary:The course of action (COA) generation is the course of designing the task planning flow, which is one of the key supporting techniques while the military organization executing aerial operation. Due to the outstanding advantage of influence nets (IN), describing the causal logic between random variable, this proposal will introduce IN into the fast building mechanism of COA model. The COA generation model utilize influence nets is established. The probability propagation method is designed, which is based on influence intensity. An improved differential evolution algorithm (IDEA) is designed to solve the action policy optimized selected model. At last, the simulated result of aerial arrack campaign case show the action policy optimized selected in variety influence constants can improve the capability of cause-effect modeling, and the improved differential evolution algorithm has fine convergent and optimized capability.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/887/1/012088