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序
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序
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第 0 章 &nbsp; 前言
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第 1 章 &nbsp; 初识算法
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第 2 章 &nbsp; 复杂度分析
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第 3 章 &nbsp; 数据结构
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第 4 章 &nbsp; 数组与链表
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第 5 章 &nbsp; 栈与队列
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第 6 章 &nbsp; 哈希表
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第 8 章 &nbsp; 堆
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第 9 章 &nbsp; 图
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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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第 14 章 &nbsp; 动态规划
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第 15 章 &nbsp; 贪心
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第 16 章 &nbsp; 附录
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<a href="../../chapter_paperbook/" class="md-nav__link ">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.5.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2023 Fonticons, Inc.--><path d="M96 0C43 0 0 43 0 96v320c0 53 43 96 96 96h320c17.7 0 32-14.3 32-32s-14.3-32-32-32v-64c17.7 0 32-14.3 32-32V32c0-17.7-14.3-32-32-32H96zm0 384h256v64H96c-17.7 0-32-14.3-32-32s14.3-32 32-32zm32-240c0-8.8 7.2-16 16-16h192c8.8 0 16 7.2 16 16s-7.2 16-16 16H144c-8.8 0-16-7.2-16-16zm16 48h192c8.8 0 16 7.2 16 16s-7.2 16-16 16H144c-8.8 0-16-7.2-16-16s7.2-16 16-16z"/></svg>
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纸质书
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<!-- Page content -->
<h1 id="111">11.1 &nbsp; 排序算法<a class="headerlink" href="#111" title="Permanent link">&para;</a></h1>
<p>「排序算法 sorting algorithm」用于对一组数据按照特定顺序进行排列。排序算法有着广泛的应用，因为有序数据通常能够被更高效地查找、分析和处理。</p>
<p><u>排序算法（sorting algorithm）</u>用于对一组数据按照特定顺序进行排列。排序算法有着广泛的应用，因为有序数据通常能够被更高效地查找、分析和处理。</p>
<p>如图 11-1 所示，排序算法中的数据类型可以是整数、浮点数、字符或字符串等。排序的判断规则可根据需求设定，如数字大小、字符 ASCII 码顺序或自定义规则。</p>
<p><a class="glightbox" href="../sorting_algorithm.assets/sorting_examples.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="数据类型和判断规则示例" class="animation-figure" src="../sorting_algorithm.assets/sorting_examples.png" /></a></p>
<p align="center"> 图 11-1 &nbsp; 数据类型和判断规则示例 </p>
<h2 id="1111">11.1.1 &nbsp; 评价维度<a class="headerlink" href="#1111" title="Permanent link">&para;</a></h2>
<p><strong>运行效率</strong>：我们期望排序算法的时间复杂度尽量低，且总体操作数量较少（时间复杂度中的常数项变小）。对于大数据量的情况，运行效率显得尤为重要。</p>
<p><strong>就地性</strong>：顾名思义，「原地排序」通过在原数组上直接操作实现排序，无须借助额外的辅助数组，从而节省内存。通常情况下，原地排序的数据搬运操作较少，运行速度也更快。</p>
<p><strong>稳定性</strong>：「稳定排序」在完成排序后，相等元素在数组中的相对顺序不发生改变。</p>
<p>稳定排序是多级排序场景的必要条件。假设我们有一个存储学生信息的表格，第 1 列和第 2 列分别是姓名和年龄。在这种情况下，「非稳定排序」可能导致输入数据的有序性丧失：</p>
<p><strong>就地性</strong>：顾名思义，<u>原地排序</u>通过在原数组上直接操作实现排序，无须借助额外的辅助数组，从而节省内存。通常情况下，原地排序的数据搬运操作较少，运行速度也更快。</p>
<p><strong>稳定性</strong>：<u>稳定排序</u>在完成排序后，相等元素在数组中的相对顺序不发生改变。</p>
<p>稳定排序是多级排序场景的必要条件。假设我们有一个存储学生信息的表格，第 1 列和第 2 列分别是姓名和年龄。在这种情况下，<u>非稳定排序</u>可能导致输入数据的有序性丧失：</p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="c1"># 输入数据是按照姓名排序好的</span>
<a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a><span class="c1"># (name, age)</span>
<a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a><span class="w"> </span><span class="o">(</span><span class="s1">&#39;A&#39;</span>,<span class="w"> </span><span class="m">19</span><span class="o">)</span>
@@ -3628,9 +3685,9 @@
<a id="__codelineno-0-15" name="__codelineno-0-15" href="#__codelineno-0-15"></a><span class="w"> </span><span class="o">(</span><span class="s1">&#39;C&#39;</span>,<span class="w"> </span><span class="m">21</span><span class="o">)</span>
<a id="__codelineno-0-16" name="__codelineno-0-16" href="#__codelineno-0-16"></a><span class="w"> </span><span class="o">(</span><span class="s1">&#39;E&#39;</span>,<span class="w"> </span><span class="m">23</span><span class="o">)</span>
</code></pre></div>
<p><strong>自适应性</strong>：「自适应排序」的时间复杂度会受输入数据的影响，即最佳时间复杂度、最差时间复杂度、平均时间复杂度并不完全相等。</p>
<p><strong>自适应性</strong>：<u>自适应排序</u>的时间复杂度会受输入数据的影响，即最佳时间复杂度、最差时间复杂度、平均时间复杂度并不完全相等。</p>
<p>自适应性需要根据具体情况来评估。如果最差时间复杂度差于平均时间复杂度，说明排序算法在某些数据下性能可能劣化，因此被视为负面属性；而如果最佳时间复杂度优于平均时间复杂度，则被视为正面属性。</p>
<p><strong>是否基于比较</strong>：「基于比较的排序」依赖比较运算符（<span class="arithmatex">\(&lt;\)</span>、<span class="arithmatex">\(=\)</span>、<span class="arithmatex">\(&gt;\)</span>）来判断元素的相对顺序，从而排序整个数组，理论最优时间复杂度为 <span class="arithmatex">\(O(n \log n)\)</span> 。而「非比较排序」不使用比较运算符，时间复杂度可达 <span class="arithmatex">\(O(n)\)</span> ，但其通用性相对较差。</p>
<p><strong>是否基于比较</strong>：<u>基于比较的排序</u>依赖比较运算符（<span class="arithmatex">\(&lt;\)</span>、<span class="arithmatex">\(=\)</span>、<span class="arithmatex">\(&gt;\)</span>）来判断元素的相对顺序，从而排序整个数组，理论最优时间复杂度为 <span class="arithmatex">\(O(n \log n)\)</span> 。而<u>非比较排序</u>不使用比较运算符，时间复杂度可达 <span class="arithmatex">\(O(n)\)</span> ，但其通用性相对较差。</p>
<h2 id="1112">11.1.2 &nbsp; 理想排序算法<a class="headerlink" href="#1112" title="Permanent link">&para;</a></h2>
<p><strong>运行快、原地、稳定、正向自适应、通用性好</strong>。显然，迄今为止尚未发现兼具以上所有特性的排序算法。因此，在选择排序算法时，需要根据具体的数据特点和问题需求来决定。</p>
<p>接下来，我们将共同学习各种排序算法，并基于上述评价维度对各个排序算法的优缺点进行分析。</p>
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