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<span class="md-ellipsis">
8.3 &nbsp; Top-K 问题
8.3 &nbsp; Top-k 问题
</span>
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<li>求解贪心问题主要分为三步：问题分析、确定贪心策略、正确性证明。其中，确定贪心策略是核心步骤，正确性证明往往是难点。</li>
<li>分数背包问题在 0-1 背包的基础上，允许选择物品的一部分，因此可使用贪心算法求解。贪心策略的正确性可以使用反证法来证明。</li>
<li>最大容量问题可使用穷举法求解，时间复杂度为 <span class="arithmatex">\(O(n^2)\)</span> 。通过设计贪心策略，每轮向内移动短板，可将时间复杂度优化至 <span class="arithmatex">\(O(n)\)</span> 。</li>
<li>在最大切分乘积问题中，我们先后推理出两个贪心策略：<span class="arithmatex">\(\geq 4\)</span> 的整数都应该继续切分、最优切分因子为 <span class="arithmatex">\(3\)</span> 。代码中包含幂运算，时间复杂度取决于幂运算实现方法，通常为 <span class="arithmatex">\(O(1)\)</span> 或 <span class="arithmatex">\(O(\log n)\)</span> 。</li>
<li>在最大切分乘积问题中，我们先后推理出两个贪心策略：<span class="arithmatex">\(\geq 4\)</span> 的整数都应该继续切分，最优切分因子为 <span class="arithmatex">\(3\)</span> 。代码中包含幂运算，时间复杂度取决于幂运算实现方法，通常为 <span class="arithmatex">\(O(1)\)</span> 或 <span class="arithmatex">\(O(\log n)\)</span> 。</li>
</ul>
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