Intrinsic noise in objective function and derivatives evaluations may cause premature termination of optimization algorithms. Evaluation complexity bounds taking this situation into account are presented in the framework of a deterministic trust-region method. The results show that the presence of intrinsic noise may dominate these bounds, in contrast with what is known for methods in which the inexactness in function and derivatives' evaluations is fully controllable. Moreover, the new analysis provides estimates of the optimality level achievable, should noise cause early termination. It finally sheds some light on the impact of inexact computer arithmetic on evaluation complexity.
翻译：客观功能和衍生物评价中固有的噪音可能导致优化算法的过早终止;在确定性信任区域方法的框架内提出了考虑到这种情况的评价复杂性界限;结果显示,内在噪音的存在可能支配这些界限,而已知的方法是功能和衍生物评价不准确,完全可以控制;此外,新分析提供了对最佳性水平的估计,如果噪音导致早期终止,则新分析提供了对最佳性水平的估计;最后,它在一定程度上说明了不精确的计算机算术对评价复杂性的影响。
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