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第 8 章 &nbsp; 堆積
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第 11 章 &nbsp; 排序
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第 12 章 &nbsp; 分治
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第 13 章 &nbsp; 回溯
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<h1 id="135">13.5 &nbsp; 小結<a class="headerlink" href="#135" title="Permanent link">&para;</a></h1>
<h3 id="1">1. &nbsp; 重點回顧<a class="headerlink" href="#1" title="Permanent link">&para;</a></h3>
<ul>
<li>回溯演算法本質是窮舉法,透過對解空間進行深度優先走訪來尋找符合條件的解。在搜尋過程中,遇到滿足條件的解則記錄,直至找到所有解或走訪完成後結束。</li>
<li>回溯演算法的搜尋過程包括嘗試與回退兩個部分。它透過深度優先搜尋來嘗試各種選擇,當遇到不滿足約束條件的情況時,則撤銷上一步的選擇,退回到之前的狀態,並繼續嘗試其他選擇。嘗試與回退是兩個方向相反的操作。</li>
<li>回溯問題通常包含多個約束條件,它們可用於實現剪枝操作。剪枝可以提前結束不必要的搜尋分支,大幅提升搜尋效率。</li>
<li>回溯演算法主要可用於解決搜尋問題和約束滿足問題。組合最佳化問題雖然可以用回溯演算法解決,但往往存在效率更高或效果更好的解法。</li>
<li>全排列問題旨在搜尋給定集合元素的所有可能的排列。我們藉助一個陣列來記錄每個元素是否被選擇,剪掉重複選擇同一元素的搜尋分支,確保每個元素只被選擇一次。</li>
<li>在全排列問題中,如果集合中存在重複元素,則最終結果會出現重複排列。我們需要約束相等元素在每輪中只能被選擇一次,這通常藉助一個雜湊集合來實現。</li>
<li>子集和問題的目標是在給定集合中找到和為目標值的所有子集。集合不區分元素順序,而搜尋過程會輸出所有順序的結果,產生重複子集。我們在回溯前將資料進行排序,並設定一個變數來指示每一輪的走訪起始點,從而將生成重複子集的搜尋分支進行剪枝。</li>
<li>對於子集和問題,陣列中的相等元素會產生重複集合。我們利用陣列已排序的前置條件,透過判斷相鄰元素是否相等實現剪枝,從而確保相等元素在每輪中只能被選中一次。</li>
<li><span class="arithmatex">\(n\)</span> 皇后問題旨在尋找將 <span class="arithmatex">\(n\)</span> 個皇后放置到 <span class="arithmatex">\(n \times n\)</span> 尺寸棋盤上的方案,要求所有皇后兩兩之間無法攻擊對方。該問題的約束條件有行約束、列約束、主對角線和次對角線約束。為滿足行約束,我們採用按行放置的策略,保證每一行放置一個皇后。</li>
<li>列約束和對角線約束的處理方式類似。對於列約束,我們利用一個陣列來記錄每一列是否有皇后,從而指示選中的格子是否合法。對於對角線約束,我們藉助兩個陣列來分別記錄該主、次對角線上是否存在皇后;難點在於找處在到同一主(副)對角線上格子滿足的行列索引規律。</li>
</ul>
<h3 id="2-q-a">2. &nbsp; Q &amp; A<a class="headerlink" href="#2-q-a" title="Permanent link">&para;</a></h3>
<p><strong>Q</strong>:怎麼理解回溯和遞迴的關係?</p>
<p>總的來看,回溯是一種“演算法策略”,而遞迴更像是一個“工具”。</p>
<ul>
<li>回溯演算法通常基於遞迴實現。然而,回溯是遞迴的應用場景之一,是遞迴在搜尋問題中的應用。</li>
<li>遞迴的結構體現了“子問題分解”的解題範式,常用於解決分治、回溯、動態規劃(記憶化遞迴)等問題。</li>
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