intuitionistic fuzzy soft set :

This article covers the definition of intuitionistic fuzzy soft set and common operations of intuitionistic fuzzy soft set. Learn about IFSS membership values, IFSS non-membership values, and study an intuitionistic fuzzy soft set with example for hybrid decision-making.

What is an Intuitionistic Fuzzy Soft Set (IFSS)?

An Intuitionistic Fuzzy Soft Set is a hybrid model. It uses Soft Sets to categorize data by parameters, and Intuitionistic Fuzzy Sets to describe the membership (yes) and non-membership (no) of each item.

The Components: Each element in an IFSS is represented as a pair: (μ, ν)
μ (mu): Degree of Membership (0 to 1).
ν (nu): Degree of Non-membership (0 to 1).
Constraint: μ + ν ≤ 1.

Example Scenario (The Setup)

Imagine a company interviewing two candidates {c1, c2} based on the parameter “Experience”.

Candidate 1 (c1): (0.7, 0.2)
Meaning: 70% experienced, 20% not experienced, 10% uncertain.

Candidate 2 (c2): (0.4, 0.5)
Meaning: 40% experienced, 50% not experienced, 10% uncertain.

Operations of IFSS with Clear Examples

Let’s assume two experts, Expert A and Expert B, give their intuitionistic fuzzy opinions on a candidate for a single parameter.

1. Union (OR Operation)

The Union takes the highest membership and the lowest non-membership.

Union = ( max(μA, μB), min(νA, νB) )
Step-by-Step Example: Expert A: (0.6, 0.3)
Expert B: (0.5, 0.4)

Calculation:
Max membership: max(0.6, 0.5) = 0.6
Min non-membership: min(0.3, 0.4) = 0.3
Result: (0.6, 0.3)

2. Intersection (AND Operation)

The Intersection takes the lowest membership and the highest non-membership.

Intersection = ( min(μA, μB), max(νA, νB) )
Step-by-Step Example: Expert A: (0.6, 0.3)
Expert B: (0.5, 0.4)

Calculation:
Min membership: min(0.6, 0.5) = 0.5
Max non-membership: max(0.3, 0.4) = 0.4
Result: (0.5, 0.4)

3. Complement (NOT Operation)

The complement simply swaps the membership and non-membership degrees.

Fc = ( ν, μ )
Step-by-Step Example: Opinion: (0.7, 0.2)
Complement Calculation: Swapping the values…
Result: (0.2, 0.7)

Operations of Intuitionistic Fuzzy Soft Numbers (IFSN)

When IFSS values are treated as numbers for calculation, we use specific arithmetic formulas for Addition and Multiplication.

OperationFormula for (μ1, ν1) and (μ2, ν2)
Addition (⊕)( μ1 + μ2 – μ1μ2 , ν1ν2 )
Multiplication (⊗)( μ1μ2 , ν1 + ν2 – ν1ν2 )

Arithmetic Step-by-Step Example

Let A = (0.5, 0.3) and B = (0.4, 0.2).

1. Addition (⊕): μ Result: 0.5 + 0.4 – (0.5 × 0.4) = 0.9 – 0.20 = 0.7
ν Result: 0.3 × 0.2 = 0.06
Sum Result: (0.7, 0.06)
2. Multiplication (⊗): μ Result: 0.5 × 0.4 = 0.2
ν Result: 0.3 + 0.2 – (0.3 × 0.2) = 0.5 – 0.06 = 0.44
Product Result: (0.2, 0.44)
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Designed by: Dr. M.U. Mirza

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Machine Learning Fuzzy Sets Computational Math Graph Theory
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