Merge branch 'master' into feat-stoer-wagner

Author: sairamsharan

DIRECTORY.md

@@ -173,6 +173,7 @@
             - 📄 [TarjansAlgorithm](src/main/java/com/thealgorithms/datastructures/graphs/TarjansAlgorithm.java)
             - 📄 [UndirectedAdjacencyListGraph](src/main/java/com/thealgorithms/datastructures/graphs/UndirectedAdjacencyListGraph.java)
             - 📄 [WelshPowell](src/main/java/com/thealgorithms/datastructures/graphs/WelshPowell.java)
+            - 📄 [TwoSat](src/main/java/com/thealgorithms/datastructures/graphs/TwoSat.java)
           - 📁 **hashmap**
             - 📁 **hashing**
               - 📄 [GenericHashMapUsingArray](src/main/java/com/thealgorithms/datastructures/hashmap/hashing/GenericHashMapUsingArray.java)
@@ -352,6 +353,7 @@
           - 📄 [PredecessorConstrainedDfs](src/main/java/com/thealgorithms/graph/PredecessorConstrainedDfs.java)
           - 📄 [StronglyConnectedComponentOptimized](src/main/java/com/thealgorithms/graph/StronglyConnectedComponentOptimized.java)
           - 📄 [TravelingSalesman](src/main/java/com/thealgorithms/graph/TravelingSalesman.java)
+          - 📄 [Dinic](src/main/java/com/thealgorithms/graph/Dinic.java)
         - 📁 **greedyalgorithms**
           - 📄 [ActivitySelection](src/main/java/com/thealgorithms/greedyalgorithms/ActivitySelection.java)
           - 📄 [BandwidthAllocation](src/main/java/com/thealgorithms/greedyalgorithms/BandwidthAllocation.java)

src/main/java/com/thealgorithms/datastructures/graphs/DialsAlgorithm.java

@@ -0,0 +1,114 @@
+package com.thealgorithms.datastructures.graphs;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Set;
+
+/**
+ * An implementation of Dial's Algorithm for the single-source shortest path problem.
+ * This algorithm is an optimization of Dijkstra's algorithm and is particularly
+ * efficient for graphs with small, non-negative integer edge weights.
+ *
+ * It uses a bucket queue (implemented here as a List of HashSets) to store vertices,
+ * where each bucket corresponds to a specific distance from the source. This is more
+ * efficient than a standard priority queue when the range of edge weights is small.
+ *
+ * Time Complexity: O(E + W * V), where E is the number of edges, V is the number
+ * of vertices, and W is the maximum weight of any edge.
+ *
+ * @see <a href="https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm#Dial's_algorithm">Wikipedia - Dial's Algorithm</a>
+ */
+public final class DialsAlgorithm {
+    /**
+     * Private constructor to prevent instantiation of this utility class.
+     */
+    private DialsAlgorithm() {
+    }
+    /**
+     * Represents an edge in the graph, connecting to a destination vertex with a given weight.
+     */
+    public static class Edge {
+        private final int destination;
+        private final int weight;
+
+        public Edge(int destination, int weight) {
+            this.destination = destination;
+            this.weight = weight;
+        }
+
+        public int getDestination() {
+            return destination;
+        }
+
+        public int getWeight() {
+            return weight;
+        }
+    }
+    /**
+     * Finds the shortest paths from a source vertex to all other vertices in a weighted graph.
+     *
+     * @param graph The graph represented as an adjacency list.
+     * @param source The source vertex to start from (0-indexed).
+     * @param maxEdgeWeight The maximum weight of any single edge in the graph.
+     * @return An array of integers where the value at each index `i` is the
+     * shortest distance from the source to vertex `i`. Unreachable vertices
+     * will have a value of Integer.MAX_VALUE.
+     * @throws IllegalArgumentException if the source vertex is out of bounds.
+     */
+    public static int[] run(List<List<Edge>> graph, int source, int maxEdgeWeight) {
+        int numVertices = graph.size();
+        if (source < 0 || source >= numVertices) {
+            throw new IllegalArgumentException("Source vertex is out of bounds.");
+        }
+
+        // Initialize distances array
+        int[] distances = new int[numVertices];
+        Arrays.fill(distances, Integer.MAX_VALUE);
+        distances[source] = 0;
+
+        // The bucket queue. Size is determined by the max possible path length.
+        int maxPathWeight = maxEdgeWeight * (numVertices > 0 ? numVertices - 1 : 0);
+        List<Set<Integer>> buckets = new ArrayList<>(maxPathWeight + 1);
+        for (int i = 0; i <= maxPathWeight; i++) {
+            buckets.add(new HashSet<>());
+        }
+
+        // Add the source vertex to the first bucket
+        buckets.get(0).add(source);
+
+        // Process buckets in increasing order of distance
+        for (int d = 0; d <= maxPathWeight; d++) {
+            // Process all vertices in the current bucket
+            while (!buckets.get(d).isEmpty()) {
+                // Get and remove a vertex from the current bucket
+                int u = buckets.get(d).iterator().next();
+                buckets.get(d).remove(u);
+
+                // If we've found a shorter path already, skip
+                if (d > distances[u]) {
+                    continue;
+                }
+
+                // Relax all adjacent edges
+                for (Edge edge : graph.get(u)) {
+                    int v = edge.getDestination();
+                    int weight = edge.getWeight();
+
+                    // If a shorter path to v is found
+                    if (distances[u] != Integer.MAX_VALUE && distances[u] + weight < distances[v]) {
+                        // If v was already in a bucket, remove it from the old one
+                        if (distances[v] != Integer.MAX_VALUE) {
+                            buckets.get(distances[v]).remove(v);
+                        }
+                        // Update distance and move v to the new bucket
+                        distances[v] = distances[u] + weight;
+                        buckets.get(distances[v]).add(v);
+                    }
+                }
+            }
+        }
+        return distances;
+    }
+}

src/main/java/com/thealgorithms/datastructures/graphs/TwoSat.java

@@ -0,0 +1,265 @@
+package com.thealgorithms.datastructures.graphs;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Stack;
+
+/**
+ * This class implements a solution to the 2-SAT (2-Satisfiability) problem
+ * using Kosaraju's algorithm to find strongly connected components (SCCs)
+ * in the implication graph.
+ *
+ * <p>
+ * <strong>Brief Idea:</strong>
+ * </p>
+ *
+ * <pre>
+ * 1. From each clause (a ∨ b), we can derive implications:
+ *      (¬a → b) and (¬b → a)
+ *
+ * 2. We construct an implication graph using these implications.
+ *
+ * 3. For each variable x, its negation ¬x is also represented as a node.
+ *    If x and ¬x belong to the same SCC, the expression is unsatisfiable.
+ *
+ * 4. Otherwise, we assign truth values based on the SCC order:
+ *    If SCC(x) > SCC(¬x), then x = true; otherwise, x = false.
+ * </pre>
+ *
+ * <p>
+ * <strong>Complexities:</strong>
+ * </p>
+ * <ul>
+ * <li>Time Complexity: O(n + m)</li>
+ * <li>Space Complexity: O(n + m)</li>
+ * </ul>
+ * where {@code n} is the number of variables and {@code m} is the number of
+ * clauses.
+ *
+ * <p>
+ * <strong>Usage Example:</strong>
+ * </p>
+ *
+ * <pre>
+ * TwoSat twoSat = new TwoSat(5); // Initialize with 5 variables: x1, x2, x3, x4, x5
+ *
+ * // Add clauses
+ * twoSat.addClause(1, false, 2, false); // (x1 ∨ x2)
+ * twoSat.addClause(3, true, 2, false); // (¬x3 ∨ x2)
+ * twoSat.addClause(4, false, 5, true); // (x4 ∨ ¬x5)
+ *
+ * twoSat.solve(); // Solve the problem
+ *
+ * if (twoSat.isSolutionExists()) {
+ *     boolean[] solution = twoSat.getSolutions();
+ *     for (int i = 1; i <= 5; i++) {
+ *         System.out.println("x" + i + " = " + solution[i]);
+ *     }
+ * }
+ * </pre>
+ * <p><strong>Reference</strong></p>
+ * <a href="https://cp-algorithms.com/graph/2SAT.html">CP Algorithm</a> <br></br>
+ * <a href="https://en.wikipedia.org/wiki/2-satisfiability">Wikipedia - 2 SAT</a>
+ * @author Shoyeb Ansari
+ *
+ * @see Kosaraju
+ */
+class TwoSat {
+
+    /** Number of variables in the boolean expression. */
+    private final int numberOfVariables;
+
+    /** Implication graph built from the boolean clauses. */
+    private final ArrayList<Integer>[] graph;
+
+    /** Transposed implication graph used in Kosaraju's algorithm. */
+    private final ArrayList<Integer>[] graphTranspose;
+
+    /** Stores one valid truth assignment for all variables (1-indexed). */
+    private final boolean[] variableAssignments;
+
+    /** Indicates whether a valid solution exists. */
+    private boolean hasSolution = true;
+
+    /** Tracks whether the {@code solve()} method has been called. */
+    private boolean isSolved = false;
+
+    /**
+     * Initializes the TwoSat solver with the given number of variables.
+     *
+     * @param numberOfVariables the number of boolean variables
+     * @throws IllegalArgumentException if the number of variables is negative
+     */
+    @SuppressWarnings({"unchecked", "rawtypes"})
+    TwoSat(int numberOfVariables) {
+        if (numberOfVariables < 0) {
+            throw new IllegalArgumentException("Number of variables cannot be negative.");
+        }
+        this.numberOfVariables = numberOfVariables;
+        int n = 2 * numberOfVariables + 1;
+
+        graph = (ArrayList<Integer>[]) new ArrayList[n];
+        graphTranspose = (ArrayList<Integer>[]) new ArrayList[n];
+        for (int i = 0; i < n; i++) {
+            graph[i] = new ArrayList<>();
+            graphTranspose[i] = new ArrayList<>();
+        }
+        variableAssignments = new boolean[numberOfVariables + 1];
+    }
+
+    /**
+     * Adds a clause of the form (a ∨ b) to the boolean expression.
+     *
+     * <p>
+     * Example: To add (¬x₁ ∨ x₂), call:
+     * </p>
+     *
+     * <pre>{@code
+     * addClause(1, true, 2, false);
+     * }</pre>
+     *
+     * @param a         the first variable (1 ≤ a ≤ numberOfVariables)
+     * @param isNegateA {@code true} if variable {@code a} is negated
+     * @param b         the second variable (1 ≤ b ≤ numberOfVariables)
+     * @param isNegateB {@code true} if variable {@code b} is negated
+     * @throws IllegalArgumentException if {@code a} or {@code b} are out of range
+     */
+    void addClause(int a, boolean isNegateA, int b, boolean isNegateB) {
+        if (a <= 0 || a > numberOfVariables) {
+            throw new IllegalArgumentException("Variable number must be between 1 and " + numberOfVariables);
+        }
+        if (b <= 0 || b > numberOfVariables) {
+            throw new IllegalArgumentException("Variable number must be between 1 and " + numberOfVariables);
+        }
+
+        a = isNegateA ? negate(a) : a;
+        b = isNegateB ? negate(b) : b;
+        int notA = negate(a);
+        int notB = negate(b);
+
+        // Add implications: (¬a → b) and (¬b → a)
+        graph[notA].add(b);
+        graph[notB].add(a);
+
+        // Build transpose graph
+        graphTranspose[b].add(notA);
+        graphTranspose[a].add(notB);
+    }
+
+    /**
+     * Solves the 2-SAT problem using Kosaraju's algorithm to find SCCs
+     * and determines whether a satisfying assignment exists.
+     */
+    void solve() {
+        isSolved = true;
+        int n = 2 * numberOfVariables + 1;
+
+        boolean[] visited = new boolean[n];
+        int[] component = new int[n];
+        Stack<Integer> topologicalOrder = new Stack<>();
+
+        // Step 1: Perform DFS to get topological order
+        for (int i = 1; i < n; i++) {
+            if (!visited[i]) {
+                dfsForTopologicalOrder(i, visited, topologicalOrder);
+            }
+        }
+
+        Arrays.fill(visited, false);
+        int sccId = 0;
+
+        // Step 2: Find SCCs on transposed graph
+        while (!topologicalOrder.isEmpty()) {
+            int node = topologicalOrder.pop();
+            if (!visited[node]) {
+                dfsForScc(node, visited, component, sccId);
+                sccId++;
+            }
+        }
+
+        // Step 3: Check for contradictions and assign values
+        for (int i = 1; i <= numberOfVariables; i++) {
+            int notI = negate(i);
+            if (component[i] == component[notI]) {
+                hasSolution = false;
+                return;
+            }
+            // If SCC(i) > SCC(¬i), then variable i is true.
+            variableAssignments[i] = component[i] > component[notI];
+        }
+    }
+
+    /**
+     * Returns whether the given boolean formula is satisfiable.
+     *
+     * @return {@code true} if a solution exists; {@code false} otherwise
+     * @throws Error if called before {@link #solve()}
+     */
+    boolean isSolutionExists() {
+        if (!isSolved) {
+            throw new Error("Please call solve() before checking for a solution.");
+        }
+        return hasSolution;
+    }
+
+    /**
+     * Returns one valid assignment of variables that satisfies the boolean formula.
+     *
+     * @return a boolean array where {@code result[i]} represents the truth value of
+     *         variable {@code xᵢ}
+     * @throws Error if called before {@link #solve()} or if no solution exists
+     */
+    boolean[] getSolutions() {
+        if (!isSolved) {
+            throw new Error("Please call solve() before fetching the solution.");
+        }
+        if (!hasSolution) {
+            throw new Error("No satisfying assignment exists for the given expression.");
+        }
+        return variableAssignments.clone();
+    }
+
+    /** Performs DFS to compute topological order. */
+    private void dfsForTopologicalOrder(int u, boolean[] visited, Stack<Integer> topologicalOrder) {
+        visited[u] = true;
+        for (int v : graph[u]) {
+            if (!visited[v]) {
+                dfsForTopologicalOrder(v, visited, topologicalOrder);
+            }
+        }
+        topologicalOrder.push(u);
+    }
+
+    /** Performs DFS on the transposed graph to identify SCCs. */
+    private void dfsForScc(int u, boolean[] visited, int[] component, int sccId) {
+        visited[u] = true;
+        component[u] = sccId;
+        for (int v : graphTranspose[u]) {
+            if (!visited[v]) {
+                dfsForScc(v, visited, component, sccId);
+            }
+        }
+    }
+
+    /**
+     * Returns the index representing the negation of the given variable.
+     *
+     * <p>
+     * Mapping rule:
+     * </p>
+     *
+     * <pre>
+     * For a variable i:
+     *     negate(i) = i + n
+     * For a negated variable (i + n):
+     *     negate(i + n) = i
+     * where n = numberOfVariables
+     * </pre>
+     *
+     * @param a the variable index
+     * @return the index representing its negation
+     */
+    private int negate(int a) {
+        return a <= numberOfVariables ? a + numberOfVariables : a - numberOfVariables;
+    }
+}