feat: travelling-salesman-bitmasking challenge

Author: IbatoLionDev

3-HARD/Python/1-travelling-salesman-bitmasking/proposed-solution/__pycache__/tsp.cpython-312.pyc

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+# Challenge: Implement a solution for the travelling salesman problem using dynamic programming with bitmasking.
+# This challenge requires optimizing the search in an exponential state space.
+# Use object-oriented programming and follow the DRY principle.
+
+from tsp import TravellingSalesman
+
+def main():
+    graph = [
+        [0, 10, 15, 20],
+        [10, 0, 35, 25],
+        [15, 35, 0, 30],
+        [20, 25, 30, 0]
+    ]
+    tsp_solver = TravellingSalesman(graph)
+    min_cost = tsp_solver.tsp(0, 1 << 0)
+    print(f"Minimum travelling salesman cost: {min_cost}")
+
+if __name__ == "__main__":
+    main()

3-HARD/Python/1-travelling-salesman-bitmasking/proposed-solution/main.py

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+from typing import List
+
+class TravellingSalesman:
+    def __init__(self, graph: List[List[int]]):
+        self.graph = graph
+        self.n = len(graph)
+        self.ALL_VISITED = (1 << self.n) - 1
+        self.memo = [[-1] * (1 << self.n) for _ in range(self.n)]
+
+    def tsp(self, pos: int, visited: int) -> int:
+        if visited == self.ALL_VISITED:
+            return self.graph[pos][0]  # return to start
+
+        if self.memo[pos][visited] != -1:
+            return self.memo[pos][visited]
+
+        ans = float('inf')
+        for city in range(self.n):
+            if (visited >> city) & 1 == 0:
+                new_visited = visited | (1 << city)
+                cost = self.graph[pos][city] + self.tsp(city, new_visited)
+                ans = min(ans, cost)
+
+        self.memo[pos][visited] = ans
+        return ans