A graph can be defined as a group of vertices and edges that are used to connect these vertices. A graph can be seen as a cyclic tree, where the vertices (Nodes) maintain any complex relationship among them instead of having a parent-child relationship. A graph G can be defined as an ordered set G(V, E) where V(G) represents the set of vertices and E(G) represents the set of edges that are used to connect these vertices.
In this “Graph Algorithms – Data Structure and Algorithms” you will learn about the following topics:
- Introduction of Graph
- Graph Terminology
- Graph Representation
- Sequential Representation, Linked Representation
- Graph Algorithms
- Terminologies in Graph Algorithms
- Types of Graph Algorithms
- Breadth-First Search (BFS) Algorithm
- Implementation of Breadth First Search (BFS)
- Depth First Search (DFS) Algorithm
- Implementation of Depth First Search (DFS)
- Topological Sort
- Spanning Tree
- General Properties of Spanning Tree, Mathematical Properties of Spanning Tree
- Minimum Spanning Tree (MST)
- Kruskal's Algorithm, Prim's Algorithm
- Dijkstra's Algorithm
- How Dijkstra's Algorithm Works?
- Example of Dijkstra's Algorithm
- Implementation of Dijkstra’s Algorithm
- Network Flow Problems
- Residual Networks, Augmenting Path
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