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<meta charset="utf-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
<meta name="description" content="Data Structures and Algorithms Crash Course with Animated Illustrations and Off-the-Shelf Code">
<meta name="description" content="Data structures and algorithms tutorial with animated illustrations and ready-to-run code">
<meta name="author" content="krahets">
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<span class="md-ellipsis">
Chapter 1. Encounter With Algorithms
Chapter 1. Encounter with Algorithms
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<span class="md-nav__icon md-icon"></span>
Chapter 1. Encounter With Algorithms
Chapter 1. Encounter with Algorithms
</label>
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<span class="md-ellipsis">
Chapter 4. Array and Linked List
Chapter 4. Arrays and Linked Lists
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Chapter 4. Array and Linked List
Chapter 4. Arrays and Linked Lists
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<span class="md-ellipsis">
4.4 Memory and Cache *
4.4 Random-Access Memory and Cache *
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Chapter 5. Stack and Queue
Chapter 5. Stacks and Queues
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Chapter 5. Stack and Queue
Chapter 5. Stacks and Queues
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<span class="md-ellipsis">
5.3 Double-Ended Queue
5.3 Deque
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Chapter 6. Hashing
Chapter 6. Hash Table
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Chapter 6. Hashing
Chapter 6. Hash Table
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7.3 Array Representation of Tree
7.3 Array Representation of Binary Trees
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<span class="md-ellipsis">
8.2 Building a Heap
8.2 Heap Construction Operation
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8.3 Top-K Problem
8.3 Top-k Problem
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10.2 Binary Search Insertion
10.2 Binary Search Insertion Point
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10.3 Binary Search Edge Cases
10.3 Binary Search Boundaries
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10.5 Search Algorithms Revisited
10.5 Searching Algorithms Revisited
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11.1 Sorting Algorithms
11.1 Sorting Algorithm
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12.4 Hanoi Tower Problem
12.4 Hanota Problem
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16.3 Terminology Table
16.3 Glossary
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<h1 id="134-n-queens-problem">13.4 &nbsp; N-Queens Problem<a class="headerlink" href="#134-n-queens-problem" title="Permanent link">&para;</a></h1>
<div class="admonition question">
<p class="admonition-title">Question</p>
<p>According to the rules of chess, a queen can attack pieces that share the same row, column, or diagonal line. Given <span class="arithmatex">\(n\)</span> queens and an <span class="arithmatex">\(n \times n\)</span> chessboard, find a placement scheme such that no two queens can attack each other.</p>
<p>According to the rules of chess, a queen can attack any piece in the same row, column, or diagonal. Given <span class="arithmatex">\(n\)</span> queens and an <span class="arithmatex">\(n \times n\)</span> chessboard, find an arrangement such that no two queens can attack each other.</p>
</div>
<p>As shown in Figure 13-15, when <span class="arithmatex">\(n = 4\)</span>, there are two solutions that can be found. From the perspective of the backtracking algorithm, an <span class="arithmatex">\(n \times n\)</span> chessboard has <span class="arithmatex">\(n^2\)</span> squares, which provide all the choices <code>choices</code>. During the process of placing queens one by one, the chessboard state changes continuously, and the chessboard at each moment represents the state <code>state</code>.</p>
<p><img alt="Solution to the 4-queens problem" class="animation-figure" src="../n_queens_problem.assets/solution_4_queens.png" /></p>
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<p align="center"> Figure 13-16 &nbsp; Constraints of the n-queens problem </p>
<h3 id="1-row-by-row-placement-strategy">1. &nbsp; Row-By-Row Placement Strategy<a class="headerlink" href="#1-row-by-row-placement-strategy" title="Permanent link">&para;</a></h3>
<p>Since both the number of queens and the number of rows on the chessboard are <span class="arithmatex">\(n\)</span>, we can easily derive a conclusion: <strong>each row of the chessboard allows and only allows exactly one queen to be placed</strong>.</p>
<p>Since both the number of queens and the number of rows on the chessboard are <span class="arithmatex">\(n\)</span>, we can easily derive a conclusion: <strong>each row of the chessboard allows one and only one queen to be placed</strong>.</p>
<p>This means we can adopt a row-by-row placement strategy: starting from the first row, place one queen in each row until the last row is completed.</p>
<p>Figure 13-17 shows the row-by-row placement process for the 4-queens problem. Due to space limitations, the figure only expands one search branch of the first row, and all schemes that do not satisfy the column constraint and diagonal constraints are pruned.</p>
<p>Figure 13-17 shows the row-by-row placement process for the 4-queens problem. Due to space limitations, the figure only expands one search branch of the first row, and all schemes that violate the column or diagonal constraints are pruned.</p>
<p><img alt="Row-by-row placement strategy" class="animation-figure" src="../n_queens_problem.assets/n_queens_placing.png" /></p>
<p align="center"> Figure 13-17 &nbsp; Row-by-row placement strategy </p>
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<p align="center"> Figure 13-18 &nbsp; Handling column and diagonal constraints </p>
<h3 id="3-code-implementation">3. &nbsp; Code Implementation<a class="headerlink" href="#3-code-implementation" title="Permanent link">&para;</a></h3>
<p>Please note that in an <span class="arithmatex">\(n\)</span>-dimensional square matrix, the range of <span class="arithmatex">\(row - col\)</span> is <span class="arithmatex">\([-n + 1, n - 1]\)</span>, and the range of <span class="arithmatex">\(row + col\)</span> is <span class="arithmatex">\([0, 2n - 2]\)</span>. Therefore, the number of both main diagonals and anti-diagonals is <span class="arithmatex">\(2n - 1\)</span>, meaning the length of both arrays <code>diags1</code> and <code>diags2</code> is <span class="arithmatex">\(2n - 1\)</span>.</p>
<p>Please note that in an <span class="arithmatex">\(n \times n\)</span> square matrix, the range of <span class="arithmatex">\(row - col\)</span> is <span class="arithmatex">\([-n + 1, n - 1]\)</span>, and the range of <span class="arithmatex">\(row + col\)</span> is <span class="arithmatex">\([0, 2n - 2]\)</span>. Therefore, the number of both main diagonals and anti-diagonals is <span class="arithmatex">\(2n - 1\)</span>, meaning the length of both arrays <code>diags1</code> and <code>diags2</code> is <span class="arithmatex">\(2n - 1\)</span>.</p>
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