Finding ε-Global Optimal Value of a One-dimensional Periodic Function in an Interval Based on Fourier Series and Semi-definite Programming

H. Chen, Churen Sun
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Abstract

One-dimensional global optimization of a function f(x) in an interval D is still a difficult problem. In this paper, we pose a new method for finding the ε-global optimal value of f(x) in D. We first approximate the function f (x) via its partial sum of its Fourier series. We show that for given ε, we can find a partial sum sn(x) n of its Fourier series such that $\math\$ when n is larger than some positive number. Then we consider finding the ε-global optimal value of this partial sum, which turns out to be able to be converted into a semi-definite programming problem via some transformation, hence is able to be solved by interior point method in polynomial time.
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基于傅里叶级数和半定规划求区间内一维周期函数的ε-全局最优值
函数f(x)在区间D内的一维全局优化仍然是一个难题。本文提出了一种求函数f(x)在d中的ε-全局最优值的新方法。我们首先用函数f(x)的傅里叶级数的部分和逼近函数f(x)。我们证明了对于给定的ε,我们可以找到它的傅里叶级数sn(x) n的部分和使得当n大于某个正数时,$\math\$。然后考虑寻找该部分和的ε-全局最优值,通过某种变换将其转化为半确定规划问题,从而可以用多项式时间内的内点法求解。
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