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30 October 2009 A method of COA based on multi-agent evolutionary algorithm
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Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74953P (2009)
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Planning detailed military course of action (COA) is very complex and time consuming. In this paper, a method based on multi-agent evolutionary algorithm was presented to solve COA' resource management and scheduling problems. Each individual can be seen as an agent, in order to realize the local perceptivity of agents, the environment is organized as a latticelike structure. Each agent is fixed on a lattice point and it can only interact with its neighbors .Two agent behaviors which are competition behavior and self-learning behavior are designed. In this work, constraint functions are considered as functions to be optimized like the objectives and then added in competition strategy to deal with the multi-objective aspect of resource-constrained project scheduling problems. This approach avoids the use of a penalty function to deal with constraints. At the same time, the added constraint functions could make the whole algorithm evolving feasible. The simulation results demonstrated that this approach could improve searching ability of this algorithm, and the precision of this method.
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Xin Yu, Hui Wang, and Licheng Jiao "A method of COA based on multi-agent evolutionary algorithm", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74953P (30 October 2009);

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