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<link rel="prev" href="../">
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<link rel="next" href="../build_binary_tree/">
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<link rel="next" href="../build_binary_tree_problem/">
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<link rel="icon" href="../../assets/images/favicon.png">
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<meta name="generator" content="mkdocs-1.4.2, mkdocs-material-9.1.11">
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@@ -1883,7 +1885,7 @@
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<li class="md-nav__item">
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<a href="../build_binary_tree/" class="md-nav__link">
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<a href="../build_binary_tree_problem/" class="md-nav__link">
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12.2. 构建树问题(New)
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../hanota_problem/" class="md-nav__link">
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12.3. 汉诺塔问题(New)
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</a>
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</li>
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</ul>
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</nav>
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</li>
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<h1 id="121">12.1. 分治<a class="headerlink" href="#121" title="Permanent link">¶</a></h1>
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<h1 id="121">12.1. 分治算法<a class="headerlink" href="#121" title="Permanent link">¶</a></h1>
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<p>「分治 Divide and Conquer」,全称分而治之,是一种非常重要的算法策略。分治通常基于递归实现,包括“分”和“治”两部分,主要步骤如下:</p>
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<ol>
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<li><strong>分(划分阶段)</strong>:递归地将原问题分解为两个或多个子问题,直至到达最小子问题时终止;</li>
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@@ -2552,7 +2568,7 @@ n(n - 4) & > 0
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<a href="../build_binary_tree/" class="md-footer__link md-footer__link--next" aria-label="下一页: 12.2. &nbsp; 构建树问题(New)" rel="next">
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<a href="../build_binary_tree_problem/" class="md-footer__link md-footer__link--next" aria-label="下一页: 12.2. &nbsp; 构建树问题(New)" rel="next">
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