https://github.com/webintellectual/travelling-salesman-problem-busted-with-ai

We have solved famous Travelling Salesman Problem using an AI algorithm Simulated Annealing
https://github.com/webintellectual/travelling-salesman-problem-busted-with-ai

ai beyond ipynb-jupyter-notebook python3 simulated-annealing simulated-annealing-algorithm state-space-search tsp tsp-problem tsp-solver visualization

Last synced: 3 months ago
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We have solved famous Travelling Salesman Problem using an AI algorithm Simulated Annealing

• Host: GitHub
• URL: https://github.com/webintellectual/travelling-salesman-problem-busted-with-ai
• Owner: webintellectual
• Created: 2023-01-20T16:46:44.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-08-07T12:14:11.000Z (almost 2 years ago)
• Last Synced: 2025-01-12T17:09:17.111Z (4 months ago)
• Topics: ai, beyond, ipynb-jupyter-notebook, python3, simulated-annealing, simulated-annealing-algorithm, state-space-search, tsp, tsp-problem, tsp-solver, visualization
• Language: Jupyter Notebook
• Homepage:
• Size: 3.59 MB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: Readme.md

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README

        

**ALGORITHM USED** : Simulated Annealing

---

### **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)

:-------------------------:|:-------------------------:

  |  ![](Images/237_output.png)




### **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)

:-------------------------:|:-------------------------:

  |  

---

---

### **Rajasthan dataset**:

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

:-------------------------:|:-------------------------:

![](Images/raj_init.png)  |  ![](Images/raj_output.png)

---

### **MY REFERENCES**:

Helped in code implementation:

- [Haversine formula](https://www.geeksforgeeks.org/program-distance-two-points-earth/) to calculate distance b/w two locations using latitude and longitude values.

- [TSP implementation](https://github.com/pratikiiitv/cs302/blob/main/tsp_sa.m) on random data set by [Dr. Pratik Shah](https://pratikiiitv.github.io/)

- 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](https://pypi.org/project/tsplib95/) python library by [Robert Grant](https://github.com/rhgrant10)

[VLSI Datset](https://www.math.uwaterloo.ca/tsp/vlsi/index.html) provided by [Andre Rohe](https://www.linkedin.com/in/andre-rohe-647521/)

---

## ⚠ **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