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* feat: Add Stoer-Wagner Algorithm for Minimum Cut * fix: Correct Stoer-Wagner implementation * fix: Remove unused import * fix: Apply clang-format
79 lines
2.5 KiB
Java
79 lines
2.5 KiB
Java
package com.thealgorithms.graph;
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/**
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* An implementation of the Stoer-Wagner algorithm to find the global minimum cut of an undirected, weighted graph.
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* A minimum cut is a partition of the graph's vertices into two disjoint sets with the minimum possible edge weight
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* sum connecting the two sets.
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*
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* Wikipedia: https://en.wikipedia.org/wiki/Stoer%E2%80%93Wagner_algorithm
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* Time Complexity: O(V^3) where V is the number of vertices.
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*/
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public class StoerWagner {
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/**
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* Finds the minimum cut in the given undirected, weighted graph.
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*
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* @param graph An adjacency matrix representing the graph. graph[i][j] is the weight of the edge between i and j.
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* @return The weight of the minimum cut.
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*/
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public int findMinCut(int[][] graph) {
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int n = graph.length;
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if (n < 2) {
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return 0;
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}
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int[][] currentGraph = new int[n][n];
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for (int i = 0; i < n; i++) {
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System.arraycopy(graph[i], 0, currentGraph[i], 0, n);
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}
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int minCut = Integer.MAX_VALUE;
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boolean[] merged = new boolean[n];
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for (int phase = 0; phase < n - 1; phase++) {
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boolean[] inSetA = new boolean[n];
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int[] weights = new int[n];
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int prev = -1;
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int last = -1;
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for (int i = 0; i < n - phase; i++) {
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int maxWeight = -1;
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int currentVertex = -1;
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for (int j = 0; j < n; j++) {
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if (!merged[j] && !inSetA[j] && weights[j] > maxWeight) {
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maxWeight = weights[j];
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currentVertex = j;
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}
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}
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if (currentVertex == -1) {
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// This can happen if the graph is disconnected.
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return 0;
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}
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prev = last;
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last = currentVertex;
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inSetA[last] = true;
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for (int j = 0; j < n; j++) {
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if (!merged[j] && !inSetA[j]) {
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weights[j] += currentGraph[last][j];
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}
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}
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}
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minCut = Math.min(minCut, weights[last]);
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// Merge 'last' vertex into 'prev' vertex
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for (int i = 0; i < n; i++) {
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currentGraph[prev][i] += currentGraph[last][i];
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currentGraph[i][prev] = currentGraph[prev][i];
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}
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merged[last] = true;
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}
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return minCut;
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}
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}
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