Page 5 - POSTER FYP MAC-OGOS 2025

DIJKSTRA’S ALGORITHM BASED ON NEUTROSOPHIC
SET FOR SOLVING TRANSPORTATION PROBLEM

D I J K S T R A ’ S A L G O R I T H M B A S E D O N N E U T R O S O P H I C K 2 4 2 / 0 5

K242/05

S E T F O R S O L V I N G T R A N S P O R T A T I O N P R O B L E M

NORSARAH FARHANA BINTI AZHAR (2022616332)

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SUPERVISOR: DR SITI NURUL FITRIAH BINTI MOHAMAD
1 - ABSTRACT
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1 - A B S T R A C T
This study modifies the classical Dijkstra’s algorithm by incorporating Single-Valued Neutrosophic Sets (SVNS) to
solve the Shortest Path Problem (SPP) under uncertainty. The proposed method was applied to a real-world
transportation case study in Kuala Lumpur where factors such as road construction and congestion introduce
variability. By using neutrosophic values and comparing several score functions, the study demonstrates that the
proposed approach yields more reliable and adaptive routes compared to conventional methods. This model is
especially suitable for logistics, emergency response, and smart transportation planning.
2 - PROBLEM STATEMENT
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2 - P R O B L E M S T A T E M E N T 3 - OBJECTIVES
Classical Dijkstra’s algorithm assumes fixed and accurate data, To modify Dijkstra’s algorithm for solving the SPP in a
which doesn’t reflect real-world transportation conditions. neutrosophic environment.

Uncertainties like traffic, weather, and missing data reduce its To apply the proposed method to a real-world transportation

effectiveness. network.

Neutrosophic sets offer a better way to model uncertainty, so the To compare the performance of the method using various

4 - METHOD
algorithm is modified using SVNS for more reliable pathfinding score functions (Ye, Garg, Rani, Singh, Nafei).

4 - M E T H O D 5 - IMPLEMENTATION
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PROPOSED

METHODOLOGY SVNS-SPP

DIJKSTRA’S ALGORITHM

NETWORK WITH

ASSIGN TO THE PERMANENT
NEUTROSOPHIC
LABEL

SHORTEST

6 - RESULT & DISCUSSION
DISTANCE

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SUGGESTED

SHORTEST PATH COMPUTE THE TEMPORARY

USING SVNS-SPP LABEL FOR EACH NODE

DIJKSTRA’S

ALGORITHM

COMPARE THE WEIGHT USING

SCORE FUNCTION

7 - CONCLUSION & CONTRIBUTION

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7 - C O N C L U S I O N & C O N T R I B U T I O N 8 - RECOMMENDATION
The modified Dijkstra’s algorithm using SVNS improves decision-making in Integrate real-time traffic data to enhance accuracy in dynamic
uncertain transportation conditions. environments.
It provides more accurate and flexible route selection compared to the classical Test the algorithm on larger and more complex transportation

method. networks.

The approach is practical for real-world applications like logistics, emergency Explore advanced models like rough or interval-valued

response, and smart traffic systems. neutrosophic sets for better uncertainty handling.