Page 29 - POSTER FYP MAC-OGOS 2025

THE EXTENDED TOPSIS PROCEDURE FOR SINGLE-VALUE NEUTROSOPHIC

SET: A CASE STUDY IN INFORMATION TECHNOLOGY (IT)

K242/30

Prepared by: Wan Amiera Zafirah Supervisor: Dr Norzieha Mustapha

Wan Zulkifli

1 ABSTRACT 2 PROBLEM STATEMENT 4 METHODPLOGY

Classical TOPSIS requires precise data Traditional MCDM methods, including classical

and lacks flexibility under ambiguity. TOPSIS, are not suited to environments with vague,

This study proposes an extended TOPSIS conflicting, or incomplete data.

method integrated with Single-Valued Expert opinions are often lost in early aggregation,

Neutrosophic Sets (SVNS) and a and standard distance measures struggle to

parameterized distance measure to distinguish closely ranked alternatives.

better handle uncertainty. This study addresses the need for a more sensitive,

The research involves (1) formulating a flexible, and inclusive method by proposing an

new SVNS-based distance measure, (2) improved TOPSIS that operates within the SVNS

applying it to select an IT software domain while preserving individual expert

development company, and (3) validating evaluations.

the method using consistency criteria.

The findings show that the extended

method yields more stable and 3 OBJECTIVES

interpretable rankings, making it 1.To formulate a distance measure integrated

effective in uncertain decision-making with TOPSIS for SVNS.

environments. 2.To apply the extended method in selecting an

IT software development company under

uncertain conditions.

5 IMPLEMENTATION

Phase 1 : Formulate a distance measure in the

SVNS environment.

Step 5: Aggregate expert preference

The distance

measure must

satisfy the following

properties:
Step 6: Compute overall closeness degree

Phase 2 : Apply distance measure in real-world case

Step 2: Compute Ideal reference set

Phase 3 : Validity test

Criteria 1:Replacement Consistency

Criteria 2 : Transitivity

Criteria 3 : Decomposition Consistency

Step 3: Apply distance measure

Step 4: Compute overall cloceness degree.

6 RESULTS & DISCUSSION 7 RECOMMENDATIONS 8 CONCLUSION

Expand the method to handle larger datasets. This study successfully extends the

TOPSIS method into the SVNS

Integrate into real-time decision support environment using a new distance

tools. measure that is more sensitive to small

Test across more diverse domains and criteria differences and preserves expert

to validate generalizability. diversity. The method proved effective

Automate implementation using advanced for IT vendor selection and holds promise

Lastly, based on the validity test, the method that programming tools (Python, MATLAB) for for broader applications in uncertain,

was proposed met all three criteria, which means it real-world decision-making scenarios.

is reliable and consistent with evaluation data. scalability.