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Commit 39f4da8

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Merge pull request #35 from philipandreadis/philip-andreadis
Heuristic solver for tsp
2 parents 5109cca + ca8067a commit 39f4da8

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import unittest
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import sys
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# Import from different folder
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sys.path.append("Algorithms/graphtheory/nearest-neighbor-tsp/")
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import NearestNeighborTSP
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class TestNN(unittest.TestCase):
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def setUp(self):
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self.G1 = [[0,3,-1],[3,0,1],[-1,1,0]]
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self.correct_path1 = [0,1,2,0]
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# No possible solution for this one so its a dead end
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self.G2 = [[0, 2, -1,-1,-1], [2, 0,5,1,-1], [-1, 5, 0, -1, -1],[-1, 1, -1, 0, 3], [-1, -1, -1, 3, 0]]
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self.correct_path2 = [0,1,3,4]
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# No possible solution for this one so its a dead end
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self.G3 = [[0, 2, -1,-1,-1], [2, 0,5,1,-1], [-1, 5, 0, -1, -1],[-1, 1, -1, 0, -1], [-1, -1, -1, -1, 0]]
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self.correct_path3 = [0, 1, 3]
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# Multiple possible solutions
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self.G4 = [[0,1,1,1],[1,0,1,1],[1,1,0,1],[1,1,1,0]]
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self.correct_path4 = [0, 1, 2, 3, 0]
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# adjacency matrix of a graph for testing
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adjMatrix = [[0,2,5,-1,3],[2,0,2,4,-1],[5,2,0,5,5],[-1,4,5,0,2],[3,-1,5,2,0]]
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# correct rank of each node's neighbors
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correctNeighbors = [[1,4,2],[0,2,3],[1,0,3,4],[4,1,2],[3,0,2]]
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def test_0_rankNeighbors(self):
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for i in range(0,4):
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self.assertEqual(NearestNeighborTSP.rankNeighbors(i, self.adjMatrix), self.correctNeighbors[i], "Check if order is different.")
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def test_1_nnTSP(self):
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path=NearestNeighborTSP.nnTSP(self.adjMatrix)
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# Test if path is null
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self.assertIsNotNone(path,"Output is empty")
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# Test if path is not complete
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self.assertEqual(len(path),len(self.adjMatrix)+1,"Path in incomplete")
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def test_linear_graph(self):
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#print(NearestNeighbor.nnTSP(self.G2))
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path = NearestNeighborTSP.nnTSP(self.G1)
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self.assertEqual(path,self.correct_path1)
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def test_simple_graph(self):
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path = NearestNeighborTSP.nnTSP(self.G2)
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self.assertEqual(path,self.correct_path2)
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def test_disconnected_graph(self):
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path = NearestNeighborTSP.nnTSP(self.G3)
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self.assertEqual(path, self.correct_path3)
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def test_complete_graph(self):
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path = NearestNeighborTSP.nnTSP(self.G4)
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self.assertEqual(path, self.correct_path4)
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if __name__ == '__main__':
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print("Running Nearest Neighbor TSP solver tests:")
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unittest.main()
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"""
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Author: Philip Andreadis
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e-mail: philip_andreadis@hotmail.com
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This script implements a simple heuristic solver for the Traveling Salesman Problem.
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It is not guaranteed that an optimal solution will be found.
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Format of input text file must be as follows:
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1st line - number of nodes
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each next line is an edge and its respective weight
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The program is executed via command line with the graph in the txt format as input.
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"""
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import time
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import sys
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"""
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This function reads the text file and returns a 2d list which represents
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the adjacency matrix of the given graph
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"""
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def parseGraph(path):
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# Read number of vertices and create adjacency matrix
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f = open(path, "r")
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n = int(f.readline())
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adjMatrix = [[-1 for i in range(n)] for j in range(n)]
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#Fill adjacency matrix with the correct edges
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for line in f:
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edge = line.split(" ")
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edge = list(map(int, edge))
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adjMatrix[edge[0]][edge[1]] = edge[2]
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adjMatrix[edge[1]][edge[0]] = edge[2]
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for i in range(len(adjMatrix)):
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adjMatrix[i][i] = 0
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return adjMatrix
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"""
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Returns all the neighboring nodes of a node sorted based on the distance between them.
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"""
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def rankNeighbors(node,adj):
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sortednn = {}
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nList = []
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for i in range(len(adj[node])):
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if adj[node][i]>0:
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sortednn[i] = adj[node][i]
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sortednn = {k: v for k, v in sorted(sortednn.items(), key=lambda item: item[1])}
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nList = list(sortednn.keys())
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return nList
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"""
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Function implementing the logic of nearest neighbor TSP.
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Generate two lists a and b, placing the starting node in list a and the rest in list b.
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While b is not empty append to a the closest neighboring node of the last node in a and remove it from b.
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Repeat until a full path has been added to a and b is empty.
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Returns list a representing the shortest path of the graph.
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"""
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def nnTSP(adj):
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nodes = list(range(0, len(adj)))
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#print(nodes)
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weight = 0
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global length
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# Starting node is 0
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a = []
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a.append(nodes[0])
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b = nodes[1:]
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while b:
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# Take last placed node in a
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last = a[-1]
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# Find its nearest neighbor
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sortedNeighbors = rankNeighbors(last,adj)
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# If node being checked has no valid neighbors and the path is not complete a dead end is reached
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if (not sortedNeighbors) and len(a)<len(nodes):
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print("Dead end!")
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return a
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flag = True
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# Find the neighbor that has not been visited
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for n in sortedNeighbors:
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if n not in a:
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nextNode = n
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flag = False
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break
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# If all neighbors of node have been already visited a dead end has been reached
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if flag:
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print("Dead end!")
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return a
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a.append(nextNode)
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b.remove(nextNode)
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# Add the weight of the edge to the total length of the path
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weight = weight + adj[last][nextNode]
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# Finishing node must be same as the starting node
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weight = weight + adj[a[0]][a[-1]]
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length = weight
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a.append(a[0])
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return a
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if __name__ == "__main__":
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# Import graph text file
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filename = sys.argv[1]
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print("~Nearest Neighbor~")
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start = time.time()
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graph = parseGraph(filename)
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n = len(graph)
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length = 0
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# Print adjacency matrix
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print("Adjacency matrix of input graph:")
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for i in range(len(graph)):
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print(graph[i])
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start = time.time()
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path = nnTSP(graph)
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finish = time.time()-start
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# Output
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print("Path:",path)
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print("Length",length)
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print("Time:",finish)
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