论文标题
分段平滑单变量最小化的七点算法
A seven-point algorithm for piecewise smooth univariate minimization
论文作者
论文摘要
在本文中，我们构建了一种算法，用于最大程度地减少派生信息的平滑函数。该算法构建了一对二次函数，其中一个具有最小的已知函数值，并选择这些二次的相交作为下一个测试点。该算法依赖于二次函数低估了特定范围内的真实函数，该算法是使用算法进行修改的调整项来完成的。
In this paper, we construct an algorithm for minimising piecewise smooth functions for which derivative information is not available. The algorithm constructs a pair of quadratic functions, one on each side of the point with smallest known function value, and selects the intersection of these quadratics as the next test point. This algorithm relies on the quadratic function underestimating the true function within a specific range, which is accomplished using a adjustment term that is modified as the algorithm progresses.
