Abstract In this paper, two different acceleration techniques for a deterministic DIRECT ( DI viding RECT angles)-type global optimization algorithm, DIRECT-GLce , are considered. We adopt dynamic data structures for better memory usage in MATLAB implementation. We also study shared and distributed parallel implementations of the original DIRECT-GLce algorithm, and a distributed parallel version for the aggressive counterpart. The efficiency of DIRECT -type parallel versions is evaluated solving box- and generally constrained global optimizations problems with varying complexity, including a practical NASA speed reducer design problem. Numerical results show a good efficiency, especially for the distributed parallel version of the original DIRECT-GLce on a multi-core PC.

中文翻译：

---

MATLAB 在加速 DIRECT-GLce 算法以通过动态数据结构和并行化进行约束全局优化方面的经验

摘要 在本文中，考虑了确定性 DIRECT（DI viding RECT 角）型全局优化算法 DIRECT-GLce 的两种不同加速技术。我们采用动态数据结构以在 MATLAB 实现中更好地使用内存。我们还研究了原始 DIRECT-GLce 算法的共享和分布式并行实现，以及积极对应的分布式并行版本。评估 DIRECT 类型并行版本的效率，以解决具有不同复杂性的盒式和一般约束全局优化问题，包括实用的 NASA 减速器设计问题。数值结果显示了良好的效率，特别是对于多核 PC 上原始 DIRECT-GLce 的分布式并行版本。