1 import numpy as np 2 3 def nearest_neighbor_algorithm(distance_matrix, cities): 4 num_cities = len(cities) 5 unvisited_cities = set(cities[1:]) # Start from the second city 6 7 tour = [cities[0]] # Start from the first city 8 current_city = cities[0] 9 10 while unvisited_cities: 11 nearest_city = min(unvisited_cities, key=lambda city: distance_matrix[cities.index(current_city)][cities.index(city)]) 12 tour.append(nearest_city) 13 unvisited_cities.remove(nearest_city) 14 current_city = nearest_city 15 16 # Return to the starting city to complete the tour 17 tour.append(cities[0]) 18 19 return tour 20 21 def calculate_total_distance(tour, distance_matrix, cities): 22 total_distance = 0 23 for i in range(len(tour) - 1): 24 current_city = tour[i] 25 next_city = tour[i + 1] 26 total_distance += distance_matrix[cities.index(current_city)][cities.index(next_city)] 27 return total_distance 28 29 # Example distance matrix (replace this with your own) 30 distance_matrix = np.array([ 31 [0,42,33,52,29,45], 32 [42,0,26,38,49,30], 33 [33,26,0,34,27,42], 34 [52,38,34,0,35,41], 35 [29,49,27,35,0,31], 36 [45,30,42,41,31,0] 37 ]) 38 39 cities = ['A', 'B', 'C', 'D', 'E', 'F'] 40 41 # Solve TSP using the nearest neighbor algorithm 42 solution = nearest_neighbor_algorithm(distance_matrix, cities) 43 44 # Calculate the total distance of the tour 45 total_distance = calculate_total_distance(solution, distance_matrix, cities) 46 47 print("Tour:", solution) 48 print("Total Distance:", total_distance)
