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Annealing Accuracy Penalty Function Based Nonlinear Constrained Optimization Method with Genetic Algorithms

Wu Zhiyuan, Shao Huihe\ Wu Xinyu  
A new optimal method based on genetic algorithms can solve nonlinear constrained optimization problems effectively, which adopted adaptive annealing penalty factors and undifferentiable accuracy penalty function. It can use the adavantages of undifferential accuracy penalty function which can not be utilized by conventional optimal methods based on gradient. Simulation results show the algorithm having good solution precision.
【Fund】: 国家“九·五”攻关课题
【CateGory Index】: O224
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