A detailed review of the dynamic search trajectory methods for global optimization is given. In addition, a family of dynamic search trajectories methods that are created using numerical methods for solving autonomous ordinary differential equations is presented. Furthermore, a strategy for developing globally convergent methods that is applicable to the proposed family of methods is given and the corresponding theorem is proved. Finally, 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.

中文翻译：

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用于全局优化的动态搜索轨迹方法

详细回顾了用于全局优化的动态搜索轨迹方法。此外，还介绍了一系列动态搜索轨迹方法，这些方法是使用数值方法创建的，用于求解自主常微分方程。此外，给出了一种开发适用于所提出的方法族的全局收敛方法的策略，并证明了相应的定理。最后，给出了获得非单调收敛方法的理论结果，该方法利用关于目标函数的最新值的累积信息。