def solve(cities):
N = len(cities)
dist = [[0] * N for i in range(N)]
for i in range(N):
for j in range(i, N):
dist[i][j] = dist[j][i] = distance(cities[i], cities[j])
# step = min(N, 10)
step = 10**3
ans_tour = generate_greedy_tour(N, dist)
ans_path_length = sum(distance(cities[ans_tour[i]], cities[ans_tour[(i + 1) % N]]) for i in range(N))
for i in range(step):
# tmp_tour = generate_greedy_tour(N, dist, (200 * i) % N)
tour, path_length = swap_cross(cities, dist, N)
# tour, path_length = swap_cross(cities, dist, ans_tour, N)
if path_length < ans_path_length:
ans_tour = tour
ans_path_length = path_length
return ans_tour
if __name__ == '__main__':
assert len(sys.argv) > 1
tour = solve(read_input(sys.argv[1]))
print_tour(tour)
for i in range(len(tour)):
length += dist[tour[i - 1]][tour[i % len(tour)]]
return length
def solve(cities):
N = len(cities)
sum_dis = 10**9
dist = [[0] * N for i in range(N)]
dist = get_euclidean_distance(cities, N, dist)
for start in range(min(10, N)):
tour = kruskal(dist, N, start)
# tour = two_opt(tour, dist)
# tour = one_or_opt(tour, dist)
# tour = two_or_opt(tour, dist)
# 最も距離の短いものを選択
if sum_dis > total_distance(tour, dist):
ans_tour = tour
sum_dis = total_distance(tour, dist)
return ans_tour
if __name__ == '__main__':
assert len(sys.argv) > 1
cities = read_input(sys.argv[1])
print_tour(solve(cities))
# improved=True
# total distanceが短くなる時だけ変更
new_tour = copy.copy(tour)
new_tour[i + 1], new_tour[j] = new_tour[j], new_tour[i + 1]
if calcurate_total_distance(
cities, new_tour) < calcurate_total_distance(
cities, tour):
tour = copy.copy(new_tour)
improved = True
return tour
def search_best_route(cities):
N = len(cities)
sum_dis = 10**9
# スタート地点は全てのノードで試す
for _ in range(N):
current_city = _
tour = solve(cities, current_city) # greedy
tour = solve_cross(cities, tour) # 交差を解除
if sum_dis > calcurate_total_distance(cities, tour):
ans = tour
sum_dis = calcurate_total_distance(cities, tour)
return ans
if __name__ == '__main__':
assert len(sys.argv) > 1
cities = read_input(sys.argv[1])
print_tour(search_best_route(cities))
return tour
def opt_2(tour, cities):
for i in range(100000):
point1 = int(random.uniform(1, len(tour)))
point2 = int(random.uniform(1, len(tour)))
while point2 == point1:
point2 = int(random.uniform(1, len(tour)))
orig = cal_dist(tour, cities)
tour[point1], tour[point2] = tour[point2], tour[point1]
updated = cal_dist(tour, cities)
if orig < updated:
tour[point1], tour[point2] = tour[point2], tour[point1]
return tour
def cal_dist(tour, cities):
dist = 0
for i in range(len(tour)-1):
# for i in range(tour-1):
dist += distance(cities[tour[i]], cities[tour[i+1]])
dist += distance(cities[tour[len(tour)-1]], cities[0])
return dist
if __name__ == '__main__':
assert len(sys.argv) > 1
tmp_tour = greedy(read_input(sys.argv[1]))
tour = opt_2(tmp_tour[:], read_input(sys.argv[1]))
print_tour(tour)
# print(cal_dist(tour, read_input(sys.argv[1])))
print("Trial No.", i + 1, "Starting from node:", current_city)
unvisited_cities = set(range(0, N))
unvisited_cities.remove(current_city)
path = [current_city]
while unvisited_cities:
next_city = min(unvisited_cities,
key=lambda city: dist[current_city][city])
unvisited_cities.remove(next_city)
path.append(next_city)
current_city = next_city
path = two_opt(path, input)
if total_distance(path, input) < best_dist:
best_path = path
return best_path
def write_output(path: list[int]):
output = open("output_6.csv", "w")
output.write("index\n")
for node in path:
output.write(str(node) + "\n")
output.close
if __name__ == '__main__':
input = read_input("input_6.csv")
path = greedy_algorithm(input)
write_output(path)
print_tour(path)
def solve(cities):
N = len(cities) #リストの長さを求める
dist = [[0] * N for i in range(N)]
for i in range(N): #リストの長さ分だけfor文が回る
for j in range(i, N): #iが今いる場所、jが次の地点の場所
dist[i][j] = dist[j][i] = distance(cities[i], cities[j]) #距離を求めている
print("distance : ", i, j, dist[i][j]) # distance 0は同じ地点を指している
current_city = 0 #初期値、０からスタート
unvisited_cities = set(range(1, N)) #訪れていない場所をobject型？でセットしている
tour = [current_city] #初期値をtourでセットしている
while unvisited_cities: #訪れてない場所全部を見ている
next_city = min(
unvisited_cities,
key=lambda city: dist[current_city][city]) #最小値のものをnext_cityに入れる
unvisited_cities.remove(next_city) #訪れていない場所から次のものを除外
tour.append(next_city) #返す用のリストtourにappend
current_city = next_city #今いる場所をcurrent_cityとして返している
return tour
if __name__ == '__main__':
assert len(sys.argv) > 1 #assertは想定と違ったら止まる（エラー処理）
tour = solve(read_input(
sys.argv[1])) #引数の１つ目を呼び出す、read_inputでファイルの読み込みを行っている
print_tour(tour) #tour (list型) を呼び出す
