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<ul>
<li>分治算法是一种常见的算法设计策略,包括分(划分)和治(合并)两个阶段,通常基于递归实现。</li>
<li>判断是否是分治算法问题的依据包括:问题能否被分解、子问题是否独立、子问题是否可以被合并。</li>
<li>归并排序是分治策略的典型应用,其递归地将数组划分为等长的两个子数组,直到只剩一个元素时开始逐层合并,从而完成排序。</li>
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<li>引入分治策略往往可以带来算法效率的提升。一方面,分治策略减少了操作数量;另一方面,分治后有利于系统的并行优化。</li>
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<li>分治既可以解决许多算法问题,也广泛应用于数据结构与算法设计中,处处可见其身影。</li>
<li>相较于暴力搜索,自适应搜索效率更高。时间复杂度为 <span class="arithmatex">\(O(\log n)\)</span> 的搜索算法通常都是基于分治策略实现的。</li>
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<li>在构建二叉树问题中,构建树(原问题)可以被划分为构建左子树和右子树(子问题),其可以通过划分前序遍历和中序遍历的索引区间来实现。</li>
<li>在汉诺塔问题中,一个规模为 <span class="arithmatex">\(n\)</span> 的问题可以被划分为两个规模为 <span class="arithmatex">\(n-1\)</span> 的子问题和一个规模为 <span class="arithmatex">\(1\)</span> 的子问题。按顺序解决这三个子问题后,原问题随之得到解决。</li>
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