Representation of Relation in Graphs and Matrices

Understanding how to represent relations in graphs and matrices is fundamental in engineering mathematics. These representations are not only crucial for theoretical understanding but also have significant practical applications in various fields of engineering, computer science, and data analysis. This article will explore different ways to represent relations using graphs and matrices, their properties, and applications in engineering.

What is a Relation?

A relation is a connection or association between elements of two sets. In mathematical terms, if we have two sets A and B, a relation R from A to B is a subset of the Cartesian product A x B.

Read More: Relations in Maths

Representation of Relation in Graphs

Graphs provide a visual way to represent relations. There are different types of graphs used for this purpose, including directed graphs (digraphs) and undirected graphs. Here's a detailed look at these representations:

Directed Graphs (Digraphs)

A directed graph consists of nodes or vertices connected by directed edges or arcs. Let R is relation from set A to set B defined as (a,b) ? R, then in directed graph-it is represented as edge(an arrow from a to b) between (a,b). 

Properties

1. A relation R is reflexive if there is a loop at every node of a directed graph.
2. A relation R is irreflexive if there is no loop at any node of directed graphs.
3. A relation R is symmetric if, for every edge between distinct nodes, an edge is always present in the opposite direction.
4. A relation R is asymmetric if there are never two edges in opposite directions between distinct nodes.
5. A relation R is transitive if there is an edge from a to b and b to c, then there is always an edge from a to c.

Example:

The directed graph of relation R = {(a,a),(a,b),(b,b),(b,c),(c,c),(c,b),(c,a)} is represented as:

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Since, there is loop at every node, it is reflexive but it is neither symmetric nor antisymmetric as there is an edge from a to b but no opposite edge from b to a and also directed edge from b to c in both directions. R is not transitive as there is an edge from a to b and b to c but no edge from a to c. 

Undirected Graphs

In an undirected graph, edges have no direction. This type of representation is used when the relation is symmetric, meaning if a is related to b, then b is also related to a.

Example:

If the relation R on set A = {1,2,3} is such that R={(1,2),(2,3)}, the undirected graph will have vertices 1, 2, and 3, with edges between 1 and 2, and 2 and 3.

Types of Relation in Graphs and Matrices

1. Combining Relation:

Suppose R is a relation from set A to B and S is a relation from set B to C, the combination of both the relations is the relation which consists of ordered pairs (a,c) where a ∈ A and c ∈ C and there exist an element b ∈ B for which (a,b) ∈ R and (b,c) ∈ S. This is represented as RoS. 

2. Inverse Relation:

A relation R is defined as (a,b) ? R from set A to set B, then the inverse relation is defined as (b,a) ? R from set B to set A. Inverse Relation is represented as R^-1

R^-1 = {(b,a) | (a,b) ? R}. 

3. Complementary Relation:

Let R be a relation from set A to B, then the complementary Relation is defined as {(a,b) } where (a,b) is not. R. 

Representation of Relation in Graphs and Matrices

Matrices provide an algebraic way to represent relations. The relation matrix is a two-dimensional array where the rows represent elements of set A and the columns represent elements of set B. If there is a relation between a_i ∈ A and b_j ∈ B, then the entry mij in the matrix is 1; otherwise, it is 0.

Applications in Engineering

Relations and their representations are widely used in engineering for various purposes:

1. Network Analysis

Graphs and matrices are extensively used in network analysis, including communication networks, transportation networks, and electrical grids. They help in understanding the connectivity and flow of information or resources.

2. Control Systems

In control systems engineering, state transition graphs and matrices represent system states and transitions, aiding in the design and analysis of control strategies.

3. Data Structures and Algorithms

In computer science, graphs and matrices are fundamental in designing algorithms for searching, sorting, and optimization problems.

4. Database Management

Relations form the basis of relational databases, where tables (matrices) are used to store and manage data efficiently.

Practice Problems on Representation of Relation in Graphs and Matrices

Problem 1:

Problem 2: Given the set A={1,2,3,4,5} and the relation R={(1,2),(2,3),(3,4),(4,5)}, represent this relation using a graph and an adjacency matrix. Check if the relation is reflexive, symmetric, or transitive.

Problem 3:

Problem 4:

Problem 5: For the set C={a,b,c}, a relation T is given as T={(a,b),(b,a),(b,c)}. Create the corresponding graph and adjacency matrix. Verify if the relation is symmetric and transitive.

Problem 6: .

Problem 7:

Problem 8:

Problem 9: For the set H={a,b,c,d}, a relation Y is defined as Y={(a,a),(b,b),(c,c),(d,d)}. Create the corresponding graph and matrix. Determine the properties of this relation.

Problem 10: .

Related Articles:

• Discrete Mathematics | Representing Relations
• Graph Matrices in Software Testing
• System of Linear Equations
• Set Theory
• Applications of Graph Theory

Conclusion

Understanding the representation of relations in graphs and matrices is crucial for various fields of engineering and computer science. These representations provide a clear and structured way to visualize and analyze connections between elements, aiding in the development of efficient solutions to complex problems.