webintellectual / Travelling-Salesman-Problem-busted-with-AI

We have solved famous Travelling Salesman Problem using an AI algorithm Simulated Annealing

ALGORITHM USED : Simulated Annealing

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131 VLSI Data Points:

Optimal Path (length = 564)	Our Output by SA (length = 646)

237 VLSI Data Points:

Optimal Path (length = 1019)	Our Output by SA (length = 1156)

343 VLSI Data Points:

Optimal Path (length = 1368)	Our Output by SA (length = 1464)

379 VLSI Data Points:

Optimal Path (length = 1332)	Our Output by SA (length = 1518)

380 VLSI Data Points:

Optimal Path (length = 1621)	Our Output by SA (length = 1941)

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Rajasthan dataset:

Initial Random Path (5272.22 km)	Output by SA (2148.81 km)

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MY REFERENCES:

Helped in code implementation:

• Haversine formula to calculate distance b/w two locations using latitude and longitude values.
• TSP implementation on random data set by Dr. Pratik Shah
• For conversion of longtidue, latitude to x-y cordinates: https://gis.stackexchange.com/questions/212723/how-can-i-convert-lon-lat-coordinates-to-x-y
• TSPLIB 95 python library by Robert Grant

VLSI Datset provided by Andre Rohe

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⚠ CAUTION:

© You must take permission from me before using this code in your work/project.
Following attributes are mandatory:
GitHub: https://github.com/webintellectual/Travelling-Salesman-Problem-busted-with-AI
Linkedin: https://www.linkedin.com/in/akshay-189a48200/
Medium: https://medium.com/@warriorak77