论文标题
不精确的恢复以最大程度地减少目标函数和约束
Inexact Restoration for Minimization with Inexact Evaluation both of the Objective Function and the Constraints
论文作者
论文摘要
在最近的一篇论文中，从最坏情况的功能复杂性和收敛的角度分析了一种用于解决连续约束优化问题的不精确恢复方法。另一方面，在一项不同的研究中，采用了不精确的恢复方法来处理不精确评估和简单约束的最小化问题。本报告中将这两种方法合并为有限的最小化问题，其中目标函数和约束及其衍生物都遵守评估错误。将证明该方法的完整描述，将证明复杂性和收敛结果。
In a recent paper an Inexact Restoration method for solving continuous constrained optimization problems was analyzed from the point of view of worst-case functional complexity and convergence. On the other hand, the Inexact Restoration methodology was employed, in a different research,to handle minimization problems with inexact evaluation and simple constraints. These two methodologies are combined in the present report, for constrained minimization problems in which both the objective function and the constraints, as well as their derivatives, are subject to evaluation errors. Together with a complete description of the method, complexity and convergence results will be proved.
