1. C++ Programming examples on “Clique”
Binary search tree algorithm can locate a node in an n node tree in order log(n) time. N-ary tree is represented by storing an array or list of child pointers with every node. A planar graph is a graph that can be drawn in the plane without any edge crossings. This section contains a C++ programs to find the maximum size clique and largest clique in a planar graphs, finds the size of largest independent set in a binary and n-ary tree, finds the clique and compares it with the size of the graph and performs graph coloring.
C++ Program to Find the Maximum Size Clique in a Graph
C++ Program to Find a Clique by Using the Technique of the Most Dense Subgraph
C++ Program to Find the Largest clique in a Planar Graph
C++ Program to Solve the Decision Problem of Testing Whether a Graph Contains a Clique Larger than a Given Size
C++ Program to Find a Maximum Weight Clique in a Weighted Graph
C++ Program to Find All the Cliques of a Given Size k
C++ Program to Find the Largest Independent Set in a Graph by Comravplements and Find the Clique of this Graph
C++ Program to Find Independent Sets in a Graph by Graph Coloring
C++ Program to Find the Maximum Independent Set of a Tree in Linear Time
C++ Program to Find Size of the Largest Independent Set(LIS) in a Given a Binary Tree
C++ Program to Find Size of the Largest Independent Set(LIS) in a Given an N-ary Tree
2. C++ Programming examples on “Vertex Cover”
A vertex cover of an undirected graph is a subset of its vertices such that for every edge (u, v) of the graph, either ‘u’ or ‘v’ is in vertex cover. The following section contains C++ programs to check whether vertex cover size k exists or not, implements heuristic to find the vertex cover in a graph and solves dominating set problem.
C++ Program to Implement a Heuristic to Find the Vertex Cover of a Graph
C++ Program to Solve the Dominating Set Problem
C++ Program to Check Whether a Vertex Cover of Size k Exists
3. C++ Programming examples on “Traveling Salesman Problem”
Travelling Salesman Problem which computes the minimum cost required to visit all the nodes by traversing across the edges only once. Held–Karp algorithm, is a dynamic programming algorithm to solve the Traveling Salesman Problem. The following Section Contains C++ programs to solve TSP using minimum spanning trees, incremental insertion method and graphs. It also finds the k-optimal tour for TSP, implements branch and bound method, held-karp algorithm and TSP using nearest neighbour algorithm.
C++ Program to Solve Travelling Salesman Problem for Unweighted Graph
C++ Program to Implement Branch and Bound Method to Perform a Combinatorial Search
C++ Program to Solve TSP Using Minimum Spanning Trees
C++ Program to Solve TSP Using Incremental Insertion Method
C++ Program to Find a k-Optimal Tour for TSP
C++ Program to Implement Held-Karp Algorithm
C++ Program to Implement Nearest Neighbour Algorithm
C++ Program to Implement Traveling Salesman Problem using Nearest Neighbour Algorithm
4. C++ Programming examples on “Hamiltonian Cycle”
Hamiltonian cycle or path in a graph is a special case of the traveling salesman problem, one where each pair of vertices with an edge between them has distance 1, while nonedge vertex pairs are separated by distance infinity. This section contains C++ programs to find the hamiltonian cycle in a graph and checks whether the given graph is hamiltonian or not. it also converts hamiltonian cycle into path.
C++ Program to Find Hamiltonian Cycle in an UnWeighted Graph
C++ Program to Find the Longest Path in a DAG
C++ Program to Check if a Given Graph must Contain Hamiltonian Cycle or Not
C++ Program to Convert Hamiltonian Cycle into Path
C++ Program to Check Whether a Hamiltonian Cycle or Path Exists in a Given Graph
5. C++ Programming examples on “Graph Partition”
Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. This section contains C++ programs to find the minimum edges and maximum cut in a graph, performs spectral partitioning of graph and tree partition using DFS.
C++ Program to Find Minimum Number of Edges to Cut to make the Graph Disconnected
C++ Program to Partition a Tree from a Given Element using DFS
C++ Program to Find the Maximum Cut in a Graph
C++ Program to Perform Spectral Partitioning of a Graph
6. C++ Programming examples on “Vertex Coloring”
Bipartite Graph is a graph in which the set of vertices can be divided into two sets such that all vertex should be present in either set 1 or set 2 but not both, and there should no edge between vertices belonging to same set. The graph coloring is a way of coloring the vertices of a graph such that no two adjacent vertices share the same color. The C++ programs in this section performs greedy coloring, graph and edge coloring on bipartite graphs, checks whether given graph is bipartite or not and implements 4-color problem, it also performs vertex coloring graph by using color interchange method.
C++ Program to Perform Graph Coloring on Bipartite Graphs
C++ Program to Check if a Given Graph is Bipartite
C++ Program to Perform Edge Coloring of a Graph
C++ Program to Use Color Interchange Method to Perform Vertex Coloring of Graph
C++ Program to Demonstrate the Implementation of 4-Color Problem
C++ Program to Perform Greedy Coloring
7. C++ Programming examples on “Edge Coloring”
Vizing’s theorem states that the edges of every simple undirected graph may be colored using a number of colors that is at most one larger than the maximum degree of the graph. The C++ programs in this section performs edge coloring on graphs, finds the chromatic index and arboricity of a graph, implements vizing’s theorem and solves open shop scheduling problems.
C++ Program to Implement the Vizing’s Theorem
C++ Program to Find Chromatic Index of Cyclic Graphs
C++ Program to Perform Edge Coloring on Complete Graph
C++ Program to Perform Edge Coloring to the Line Graph of an Input Graph
C++ Program to Find the Arboricity of a Graph
C++ Program to Solve the Open Shop Scheduling Problem
8. C++ Programming examples on “Steiner Tree”
Steiner Tree may contain some vertices which are not in given subset but are used to connect the vertices of subset. This section contains C++ programs to find the Steiner tree and its size of a graph, it also explains the program to apply heuristic based shortest path to find the steiner tree.
C++ Program to Find the Steiner Tree of a Given Graph
C++ Program to Apply Heuristic Based on Shortest Path to Find Steiner Tree
C++ Program to Check if a Steiner Tree Size k Exists for a Graph
9. C++ Programming examples on “Feedback Edge/Vertex Set”
Feedback edge and vertex set in a graph is the set which contains edges/vertex which when removed from the graph, graph becomes directed acyclic graph. This section contains C++ programs to find the good feedback edge and vertex set in a graph and checks whether graph is DAG.
C++ Program to Check Whether Graph is DAG
C++ Program to Find a Good Feedback Edge Set in a Graph
C++ Program to Find a Good Feedback Vertex Set