This project is to exercise on designing and implementing an evolutionary algorithm to solve the Traveling Salesman Problem (TSP) IN PYTHON PROGRAMMING LANGUAGE with the given instances following the workflow:

1. Design a(standard/conventional) EA for TSP with operations discussed from the course

2. Implement at least one advanced technique from published research articles at your own choice (e.g., parameter self-adaptation, improved mutation/crossover, diversity preservation, etc.) to improve your EA

3. Test your EA on the TSP instance of Western Sahara (29 cities). Given Below

*****WesternSahara_29*****

1 20833.3333 17100.0000

2 20900.0000 17066.6667

3 21300.0000 13016.6667

4 21600.0000 14150.0000

5 21600.0000 14966.6667

6 21600.0000 16500.0000

7 22183.3333 13133.3333

8 22583.3333 14300.0000

9 22683.3333 12716.6667

10 23616.6667 15866.6667

11 23700.0000 15933.3333

12 23883.3333 14533.3333

13 24166.6667 13250.0000

14 25149.1667 12365.8333

15 26133.3333 14500.0000

16 26150.0000 10550.0000

17 26283.3333 12766.6667

18 26433.3333 13433.3333

19 26550.0000 13850.0000

20 26733.3333 11683.3333

21 27026.1111 13051.9444

22 27096.1111 13415.8333

23 27153.6111 13203.3333

24 27166.6667 9833.3333

25 27233.3333 10450.0000

26 27233.3333 11783.3333

27 27266.6667 10383.3333

28 27433.3333 12400.0000

29 27462.5000 12992.2222