On the Golf Method

TL;DR: In this article, the authors introduce a new method for the global unconstrained minimization of a differentiable objective function based on search trajectories, which are defined by a differential equation and exhibit certain similarities to the trajectories of steepest descent.

TL;DR: A review of the methods for global optimization reveals that most methods have been developed for unconstrained problems and need to be extended to general constrained problems because most of the engineering applications have constraints.

TL;DR: T theoretical results for obtaining nonmonotone convergent methods that exploit the accumulated information with regard to the most recent values of the objective function are given.

TL;DR: A new class of methods for training multilayer feedforward neural networks draws from methods for solving initial value problems of ordinary differential equations, and belong to the subclass of trajectory methods.