Over the last three decades, many attempts have been made to improve the DIRECT (DIviding RECTangles) algorithm's efficiency. Various novel ideas and extensions have been suggested. The main two steps of DIRECT-type algorithms are the selection and partitioning of potentially optimal candidates. However, the most efficient combination of these two steps is an area that has not been investigated so far. This paper presents a study covering an extensive examination of various candidate selection and partitioning techniques within the same DIRECT algorithmic framework. Twelve DIRECT-type algorithmic variations are compared on 800 randomly generated GKLS-type test problems and 94 box-constrained global optimization problems from DIRECTlib with varying complexity. We have identified the most efficient selection and partitioning combinations based on these studies, leading to new, more efficient, DIRECT-type algorithms.
翻译：在过去三十年中,为了提高直接(DIviding RECTangles)算法的效率,已经做出了许多尝试。提出了各种新的想法和扩展建议。直接型算法的主要两个步骤是选择和分解潜在最佳候选人。然而,这两个步骤最有效的结合是迄今尚未调查的一个领域。本文件介绍了一项研究,涉及对同一直接算法框架内的各种候选人选择和分解技术的全面审查。12个直接型算法变换比较了800个随机产生的GKLS型测试问题和94个由不同复杂程度的直接型决定的受箱控全球优化问题。我们根据这些研究确定了最高效的选择和分解组合,导致新的、更有效率的、直接型算法。
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