Solving TSP in Python with Data in Excel

Hello everyone and welcome. In this post, I’m going to show you how to solve travelling salesman problems (TSP) using 2-opt algorithm in Python with the city locations are imported from Excel file. This method is very simple but very effective. To solve new TSP instances, you just need to update the data in the Excel file. The rest of the Python code can be kept the same.

Here is the format of the data related to city locations in Excel. Please keep in mind that the Excel file and the Python file must be put in the same folder.

If you want some basic information about 2 opt algorithm, please have a look at this page.

Let’s see how it works:

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Python Code

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

data = pd.read_excel('TSP Data.xlsx',index_col=0)
city_list =np.array(data)

solution = np.arange(city_list.shape[0]) 
city_locations = ...
 
plt.scatter(city_list[:,0],city_list[:,1])
plt.plot(city_locations[:,0],city_locations[:,1])
plt.title("Initial solution") 
plt.show()
  
distance_calculation = ...
swap_algorithm = ...
current_best_distance = distance_calculation(solution,city_list) 

for swap1 in range(1,len(solution)-2):
    for swap2 in range(swap1+1,len(solution)): 
        new_solution = swap_algorithm(solution,swap1,swap2) 
        new_distance = distance_calculation(new_solution,city_list)
        if new_distance < current_best_distance: 
            solution = new_solution 
            current_best_distance = new_distance 
 
plt.figure()
city_locations = ...
plt.scatter(city_list[:,0],city_list[:,1])
plt.plot(city_locations[:,0],city_locations[:,1])
plt.title("Final solution") 
plt.show()
     
print('final solution', solution)    
print('best distance: ', distance_calculation(solution,city_list)) 
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