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An uncertain optimization method based on interval differential evolution and adaptive subinterval decomposition analysis

机译:基于区间差分演化和自适应子区间分解分析的不确定性优化方法

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摘要

An interval differential evolution (IDE) with adaptive subinterval decomposition analysis is suggested to directly solve the nonlinear uncertain optimization problems with interval parameters. The adaptive subinterval decomposition analysis technique is proposed to calculate the upper and lower bounds of objective function and constraints caused by interval uncertainties. An adaptive convergence mechanism is utilized to ensure the accuracy of achieved bounds. Moreover, within the framework of IDE, the interval possibility model is employed to deal with the interval constraints of uncertain optimization problems and the interval preferential rule is used to select the promising solutions to retain into the next evolutionary population. Both numerical and engineering examples are eventually given to demonstrate the validity of the proposed method.
机译:提出了一种采用自适应子区间分解分析的区间微分进化算法(IDE)直接解决区间参数的非线性不确定性优化问题。提出了一种自适应子区间分解分析技术来计算目标函数的上界和下界以及区间不确定性引起的约束。利用自适应收敛机制来确保所达到边界的准确性。此外,在IDE的框架内,采用区间可能性模型来处理不确定性优化问题的区间约束,并使用区间优先规则选择有前途的解决方案以保留到下一进化种群中。最后通过数值和工程实例验证了该方法的有效性。

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