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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的结构优化设计

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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:为了克服简单的遗传算法的过早现象和能够利用复杂约束优化算法,本文提出了一种改进的基于一些改进方法的遗传算法,并通过采用自适应交叉率和突变率来应用框架结构的优化设计 ,调整人口大小,健身和惩罚职能以及搜索GA的精英策略。 实验结果表明,改进的遗传算法对全局收敛性具有良好的性能,并且所提出的方法可以应用于具有离散变量的结构的最佳设计。

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