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Optimal Design of Structures with Discrete Variables Based on Improved Genetic Algorithms

机译:基于改进遗传算法的离散变量结构优化设计

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In order to overcome premature phenomenon of simple genetic algorithms and inability to optimize algorithms with complex constraints, an improved genetic algorithms based on some improved methods is presented in this paper and is applied in optimization design of frame structure by adopting adaptive crossover rate and mutation rate, adjusting population size, fitness and penalty function and elitist strategy in the search of GA. The experimental results indicate that the improved genetic algorithm has good performance on the global convergence and that the proposed method can be applied to optimal design of structures with discrete variables.
机译:为了克服简单遗传算法的过早现象和复杂约束无法优化算法的不足,提出了一种基于改进算法的改进遗传算法,并通过自适应交叉率和变异率将其应用于框架结构的优化设计中。 ,在搜寻Google Analytics(分析)时调整人口规模,适应度和惩罚功能以及精英策略。实验结果表明,改进的遗传算法在全局收敛性上具有良好的性能,可以应用于离散变量结构的优化设计。

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