Welsh-Powell plot coloring algorithm

Graphics coloring is a key issue in information technology and has wide applications in fields such as scheduling, register allocation, and map coloring. The Welsh-Powell algorithm is an efficient way to color a graph, ensuring that nearby vertices have a variety of shades while using fewer colors. In this article we will look at 2 ways to create the Welsh-Powell algorithm using the C algorithm.

usage instructions

• Sequential vertex sorting

• Maximum first vertex sorting

Sequential vertex sorting

In the first technique, colors are assigned to vertices in descending order of their degree. This technique ensures that vertices of greater extent that usually have more neighbors are colored first.

algorithm

• Determine the level of each graph vertex.

• Determine the degree of the vertices and sort them in descending order.

• Set the assigned color for each vertex position in the array.

• Repeat step 2 for the vertices in the order determined here.

• Specify for each vertex the minimum color that is not yet used by its adjacent vertices.

Example

#include <iostream>
#include <vector>
#include <algorithm>

using namespace std;

// Graph structure
struct Graph {
    int V;  // Number of vertices
    vector<vector<int>> adj;  // Adjacency list

    // Constructor
    Graph(int v) : V(v), adj(v) {}

    // Function to add an edge between two vertices
    void addEdge(int u, int v) {
        adj[u].push_back(v);
        adj[v].push_back(u);
    }
};

// Function to compare vertices based on weight
bool compareWeights(pair<int, int> a, pair<int, int> b) {
    return a.second > b.second;
}

// Function to perform graph coloring using Welsh-Powell algorithm
void graphColoring(Graph& graph) {
    int V = graph.V;
    vector<pair<int, int>> vertexWeights;

    // Assign weights to each vertex based on their degree
    for (int v = 0; v < V; v++) {
        int weight = graph.adj[v].size();
        vertexWeights.push_back(make_pair(v, weight));
    }

    // Sort vertices in descending order of weights
    sort(vertexWeights.begin(), vertexWeights.end(), compareWeights);

    // Array to store colors assigned to vertices
    vector<int> color(V, -1);

    // Assign colors to vertices in the sorted order
    for (int i = 0; i < V; i++) {
        int v = vertexWeights[i].first;

        // Find the smallest unused color for the current vertex
        vector<bool> usedColors(V, false);
        for (int adjVertex : graph.adj[v]) {
            if (color[adjVertex] != -1)
                usedColors[color[adjVertex]] = true;
        }

        // Assign the smallest unused color to the current vertex
        for (int c = 0; c < V; c++) {
            if (!usedColors[c]) {
                color[v] = c;
                break;
            }
        }
    }

    // Print the coloring result
    for (int v = 0; v < V; v++) {
        cout << "Vertex " << v << " is assigned color " << color[v] << endl;
    }
}

int main() {
    // Create a sample graph
    Graph graph(6);
    graph.addEdge(0, 1);
    graph.addEdge(0, 2);
    graph.addEdge(1, 2);
    graph.addEdge(1, 3);
    graph.addEdge(2, 3);
    graph.addEdge(3, 4);
    graph.addEdge(4, 5);

    // Perform graph coloring
    graphColoring(graph);

    return 0;
}

Output

Vertex 0 is assigned color 2
Vertex 1 is assigned color 0
Vertex 2 is assigned color 1
Vertex 3 is assigned color 2
Vertex 4 is assigned color 0
Vertex 5 is assigned color 1

Maximum first vertex sorting

Similar to method one, the second method involves arranging the vertices in descending order according to their degrees. This approach colors the highest degree vertex first and then recursively colors its uncolored neighbors, rather than assigning colors sequentially.

algorithm

• Determine the degree of each graph vertex.

• Determine the degree of the vertices and sort them in descending order.

• Set the assigned color for each vertex position in the array.

• Start shading from the vertex of maximum degree.

• Select the smallest color available for each neighbor of the currently uncolored vertex.

Example

#include <iostream>
#include <vector>
#include <algorithm>
#include <unordered_set>

using namespace std;

class Graph {
private:
    int numVertices;
    vector<unordered_set<int>> adjacencyList;

public:
    Graph(int vertices) {
        numVertices = vertices;
        adjacencyList.resize(numVertices);
    }

    void addEdge(int src, int dest) {
        adjacencyList[src].insert(dest);
        adjacencyList[dest].insert(src);
    }

    int getNumVertices() {
        return numVertices;
    }

    unordered_set<int>& getNeighbors(int vertex) {
        return adjacencyList[vertex];
    }
};

void welshPowellLargestFirst(Graph graph) {
    int numVertices = graph.getNumVertices();
    vector<int> colors(numVertices, -1);

    vector<pair<int, int>> largestFirst;
    for (int i = 0; i < numVertices; i++) {
        largestFirst.push_back(make_pair(graph.getNeighbors(i).size(), i));
    }

    sort(largestFirst.rbegin(), largestFirst.rend()); 
    int numColors = 0;
    for (const auto& vertexPair : largestFirst) {
        int vertex = vertexPair.second;

        if (colors[vertex] != -1) {
            continue; // Vertex already colored
        }

        colors[vertex] = numColors;

        for (int neighbor : graph.getNeighbors(vertex)) {
            if (colors[neighbor] == -1) {
                colors[neighbor] = numColors;
            }
        }

        numColors++;
    }

    // Print assigned colors
    for (int i = 0; i < numVertices; i++) {
        cout << "Vertex " << i << " - Color: " << colors[i] << endl;
    }
}

int main() {
    Graph graph(7);

    graph.addEdge(0, 1);
    graph.addEdge(0, 2);
    graph.addEdge(0, 3);
    graph.addEdge(1, 4);
    graph.addEdge(1, 5);
    graph.addEdge(2, 6);
    graph.addEdge(3, 6);

    welshPowellLargestFirst(graph);

    return 0;
}

Output

Vertex 0 - Color: 0
Vertex 1 - Color: 0
Vertex 2 - Color: 1
Vertex 3 - Color: 1
Vertex 4 - Color: 0
Vertex 5 - Color: 0
Vertex 6 - Color: 1

in conclusion

This blog post analyzes two different methods of constructing the Welsh Powell diagram coloring technique using the C algorithm. Each method adopts a different strategy when sorting vertices and assigning colors, resulting in an efficient and optimized graph coloring method. By using these techniques, we can effectively reduce the number of colors required while ensuring that nearby vertices contain different colors. With its adaptability and simplicity, the Welsh-Powell algorithm remains a useful tool in a variety of graph shading applications.

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