mirror of
https://github.com/krahets/hello-algo.git
synced 2025-07-14 19:41:41 +08:00
deploy
This commit is contained in:
@ -3441,7 +3441,7 @@
|
||||
<p>请在数组中选择两个隔板,使得组成的容器的容量最大,返回最大容量。</p>
|
||||
</div>
|
||||
<p><img alt="最大容量问题的示例数据" src="../max_capacity_problem.assets/max_capacity_example.png" /></p>
|
||||
<p align="center"> 图:最大容量问题的示例数据 </p>
|
||||
<p align="center"> 图 15-7 最大容量问题的示例数据 </p>
|
||||
|
||||
<p>容器由任意两个隔板围成,<strong>因此本题的状态为两个隔板的索引,记为 <span class="arithmatex">\([i, j]\)</span></strong> 。</p>
|
||||
<p>根据题意,容量等于高度乘以宽度,其中高度由短板决定,宽度是两隔板的索引之差。设容量为 <span class="arithmatex">\(cap[i, j]\)</span> ,则可得计算公式:</p>
|
||||
@ -3450,24 +3450,24 @@ cap[i, j] = \min(ht[i], ht[j]) \times (j - i)
|
||||
\]</div>
|
||||
<p>设数组长度为 <span class="arithmatex">\(n\)</span> ,两个隔板的组合数量(即状态总数)为 <span class="arithmatex">\(C_n^2 = \frac{n(n - 1)}{2}\)</span> 个。最直接地,<strong>我们可以穷举所有状态</strong>,从而求得最大容量,时间复杂度为 <span class="arithmatex">\(O(n^2)\)</span> 。</p>
|
||||
<h3 id="1">1. 贪心策略确定<a class="headerlink" href="#1" title="Permanent link">¶</a></h3>
|
||||
<p>这道题还有更高效率的解法。如下图所示,现选取一个状态 <span class="arithmatex">\([i, j]\)</span> ,其满足索引 <span class="arithmatex">\(i < j\)</span> 且高度 <span class="arithmatex">\(ht[i] < ht[j]\)</span> ,即 <span class="arithmatex">\(i\)</span> 为短板、 <span class="arithmatex">\(j\)</span> 为长板。</p>
|
||||
<p>这道题还有更高效率的解法。如图 15-8 所示,现选取一个状态 <span class="arithmatex">\([i, j]\)</span> ,其满足索引 <span class="arithmatex">\(i < j\)</span> 且高度 <span class="arithmatex">\(ht[i] < ht[j]\)</span> ,即 <span class="arithmatex">\(i\)</span> 为短板、 <span class="arithmatex">\(j\)</span> 为长板。</p>
|
||||
<p><img alt="初始状态" src="../max_capacity_problem.assets/max_capacity_initial_state.png" /></p>
|
||||
<p align="center"> 图:初始状态 </p>
|
||||
<p align="center"> 图 15-8 初始状态 </p>
|
||||
|
||||
<p>如下图所示,<strong>若此时将长板 <span class="arithmatex">\(j\)</span> 向短板 <span class="arithmatex">\(i\)</span> 靠近,则容量一定变小</strong>。这是因为在移动长板 <span class="arithmatex">\(j\)</span> 后:</p>
|
||||
<p>如图 15-9 所示,<strong>若此时将长板 <span class="arithmatex">\(j\)</span> 向短板 <span class="arithmatex">\(i\)</span> 靠近,则容量一定变小</strong>。这是因为在移动长板 <span class="arithmatex">\(j\)</span> 后:</p>
|
||||
<ul>
|
||||
<li>宽度 <span class="arithmatex">\(j-i\)</span> 肯定变小。</li>
|
||||
<li>高度由短板决定,因此高度只可能不变( <span class="arithmatex">\(i\)</span> 仍为短板)或变小(移动后的 <span class="arithmatex">\(j\)</span> 成为短板)。</li>
|
||||
</ul>
|
||||
<p><img alt="向内移动长板后的状态" src="../max_capacity_problem.assets/max_capacity_moving_long_board.png" /></p>
|
||||
<p align="center"> 图:向内移动长板后的状态 </p>
|
||||
<p align="center"> 图 15-9 向内移动长板后的状态 </p>
|
||||
|
||||
<p>反向思考,<strong>我们只有向内收缩短板 <span class="arithmatex">\(i\)</span> ,才有可能使容量变大</strong>。因为虽然宽度一定变小,<strong>但高度可能会变大</strong>(移动后的短板 <span class="arithmatex">\(i\)</span> 可能会变长)。例如在下图中,移动短板后面积变大。</p>
|
||||
<p>反向思考,<strong>我们只有向内收缩短板 <span class="arithmatex">\(i\)</span> ,才有可能使容量变大</strong>。因为虽然宽度一定变小,<strong>但高度可能会变大</strong>(移动后的短板 <span class="arithmatex">\(i\)</span> 可能会变长)。例如在图 15-10 中,移动短板后面积变大。</p>
|
||||
<p><img alt="向内移动短板后的状态" src="../max_capacity_problem.assets/max_capacity_moving_short_board.png" /></p>
|
||||
<p align="center"> 图:向内移动短板后的状态 </p>
|
||||
<p align="center"> 图 15-10 向内移动短板后的状态 </p>
|
||||
|
||||
<p>由此便可推出本题的贪心策略:初始化两指针分裂容器两端,每轮向内收缩短板对应的指针,直至两指针相遇。</p>
|
||||
<p>下图展示了贪心策略的执行过程。</p>
|
||||
<p>图 15-11 展示了贪心策略的执行过程。</p>
|
||||
<ol>
|
||||
<li>初始状态下,指针 <span class="arithmatex">\(i\)</span> , <span class="arithmatex">\(j\)</span> 分列与数组两端。</li>
|
||||
<li>计算当前状态的容量 <span class="arithmatex">\(cap[i, j]\)</span> ,并更新最大容量。</li>
|
||||
@ -3505,7 +3505,7 @@ cap[i, j] = \min(ht[i], ht[j]) \times (j - i)
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<p align="center"> 图:最大容量问题的贪心过程 </p>
|
||||
<p align="center"> 图 15-11 最大容量问题的贪心过程 </p>
|
||||
|
||||
<h3 id="2">2. 代码实现<a class="headerlink" href="#2" title="Permanent link">¶</a></h3>
|
||||
<p>代码循环最多 <span class="arithmatex">\(n\)</span> 轮,<strong>因此时间复杂度为 <span class="arithmatex">\(O(n)\)</span></strong> 。</p>
|
||||
@ -3695,12 +3695,12 @@ cap[i, j] = \min(ht[i], ht[j]) \times (j - i)
|
||||
</div>
|
||||
<h3 id="3">3. 正确性证明<a class="headerlink" href="#3" title="Permanent link">¶</a></h3>
|
||||
<p>之所以贪心比穷举更快,是因为每轮的贪心选择都会“跳过”一些状态。</p>
|
||||
<p>比如在状态 <span class="arithmatex">\(cap[i, j]\)</span> 下,<span class="arithmatex">\(i\)</span> 为短板、<span class="arithmatex">\(j\)</span> 为长板。若贪心地将短板 <span class="arithmatex">\(i\)</span> 向内移动一格,会导致下图所示的状态被“跳过”。<strong>这意味着之后无法验证这些状态的容量大小</strong>。</p>
|
||||
<p>比如在状态 <span class="arithmatex">\(cap[i, j]\)</span> 下,<span class="arithmatex">\(i\)</span> 为短板、<span class="arithmatex">\(j\)</span> 为长板。若贪心地将短板 <span class="arithmatex">\(i\)</span> 向内移动一格,会导致图 15-12 所示的状态被“跳过”。<strong>这意味着之后无法验证这些状态的容量大小</strong>。</p>
|
||||
<div class="arithmatex">\[
|
||||
cap[i, i+1], cap[i, i+2], \dots, cap[i, j-2], cap[i, j-1]
|
||||
\]</div>
|
||||
<p><img alt="移动短板导致被跳过的状态" src="../max_capacity_problem.assets/max_capacity_skipped_states.png" /></p>
|
||||
<p align="center"> 图:移动短板导致被跳过的状态 </p>
|
||||
<p align="center"> 图 15-12 移动短板导致被跳过的状态 </p>
|
||||
|
||||
<p>观察发现,<strong>这些被跳过的状态实际上就是将长板 <span class="arithmatex">\(j\)</span> 向内移动的所有状态</strong>。而在第二步中,我们已经证明内移长板一定会导致容量变小。也就是说,被跳过的状态都不可能是最优解,<strong>跳过它们不会导致错过最优解</strong>。</p>
|
||||
<p>以上的分析说明,<strong>移动短板的操作是“安全”的</strong>,贪心策略是有效的。</p>
|
||||
|
Reference in New Issue
Block a user