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Extended Range Guided Munition Parameter Optimization Based on Genetic Algorithms

Extended Range Guided Munition Parameter Optimization Based on Genetic Algorithms
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摘要 Many factors influencing range of extended range guided munition (ERGM) are analyzed. The definition domain of the most important three parameters are ascertained by preparatory mathematical simulation, the optimized mathematical model of ERGM maximum range with boundary conditions is created, and parameter optimization based on genetic algorithm (GA) is adopted. In the GA design, three-point crossover is used and the best chromosome is kept so that the convergence speed becomes rapid. Simulation result shows that GA is feasible, the result is good and it can be easy to attain global optimization solution, especially when the objective function is not the convex one for independent variables and it is a multi-parameter problem. Many factors influencing range of extended range guided munition (ERGM) are analyzed. The definition domain of the most important three parameters are ascertained by preparatory mathematical simulation, the optimized mathematical model of ERGM maximum range with boundary conditions is created, and parameter optimization based on genetic algorithm (GA) is adopted. In the GA design, three-point crossover is used and the best chromosome is kept so that the convergence speed becomes rapid. Simulation result shows that GA is feasible, the result is good and it can be easy to attain global optimization solution, especially when the objective function is not the convex one for independent variables and it is a multi-parameter problem.
出处 《Journal of Beijing Institute of Technology》 EI CAS 2005年第3期297-301,共5页 北京理工大学学报(英文版)
关键词 genetic algorithm(GA) parameter optimization penalty function genetic algorithm(GA) parameter optimization penalty function
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参考文献1

  • 1Kim Young-Ha,Spencer D B.Optimal spacecraft rendezvous using genetic algorithms[].Journal of Space.2002

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