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A new design optimization framework based on immune algorithm and Taguchi's method

机译:基于免疫算法和田口方法的新设计优化框架

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摘要

This paper describes an innovative optimization approach that offers significant improvements in performance over existing methods to solve shape optimization problems. The new approach is based on two-stages which are (1) Taguchi's robust design approach to find appropriate interval levels of design parameters (2) Immune algorithm to generate optimal solutions using refined intervals from the previous stage. A benchmark test problem is first used to illustrate the effectiveness and efficiency of the approach. Finally, it is applied to the shape design optimization of a vehicle component to illustrate how the present approach can be applied for solving shape design optimization problems. The results show that the proposed approach not only can find optimal but also can obtain both better and more robust results than the existing algorithm reported recently in the literature.
机译:本文介绍了一种创新的优化方法,与解决形状优化问题的现有方法相比,该方法在性能上有显着提高。新方法基于两个阶段,即(1)Taguchi的鲁棒性设计方法来找到适当的设计参数区间水平;(2)免疫算法,可以使用前一阶段的精确区间来生成最佳解决方案。首先使用基准测试问题来说明该方法的有效性和效率。最后,将其应用于车辆部件的形状设计优化,以说明如何将本方法应用于解决形状设计优化问题。结果表明,与文献中最近报道的现有算法相比,该方法不仅可以找到最优解,而且可以获得更好,更鲁棒的结果。

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