论文标题
全球优化中的子域可分离性
Subdomain Separability in Global Optimization
论文作者
论文摘要
我们提出在全球优化背景下可分离性的概括。我们的结果适用于实施的目标功能作为可区分的计算机程序。它们是在简单的分支和绑定方法的上下文中提出的。通常可以预期较大的搜索空间降低将产生任何全局优化方法的加速度。我们展示了如何利用通过伴随算法分化计算出的间隔衍生物来检查目标相对于所谓的结构分离器的单调性以及如何自动验证后者。
We propose a generalization of separability in the context of global optimization. Our results apply to objective functions implemented as differentiable computer programs. They are presented in the context of a simple branch and bound method. The often significant search space reduction can be expected to yield an acceleration of any global optimization method. We show how to utilize interval derivatives calculated by adjoint algorithmic differentiation to examine the monotonicity of the objective with respect to so called structural separators and how to verify the latter automatically.
