Christofides Algorithm for TSP.

## Project description

This package(Christofides) provides a way to implement Christofides algorithm for solving Travelling Saleman Problem(TSP) to obtain an approximate solution on an undirected graph(Distance Matrix) provided as an upper Triangular matrix. The Distance from a node on to itself is assumed 0.

## Usage

Use the compute() function which takes as input a distance_matrix and returns a Christofides solution as follows:

from Christofides import christofides
TSP = christofides.compute(distance_matrix)

or:

import Christofides
TSP = Christofides.christofides.compute(distance_matrix)

The Distance Matrix is an upper Triangular matrix with distance from a node on to itself 0, since Christofides algorithm could only be applied for undirected graphs. Also the distance between a node on to itself is practically 0. Example for distance_matrix is as follows, distance_matrix =

[[0,45,65,15],
[0,0,56,12],
[0,0,0,89],
[0,0,0,0]]

The above distance_matrix should be provided as an input to christofides.compute(), when we want to calculate TSP for distance =

[[0,45,65,15],
[45,0,56,12],
[65,56,0,89],
[15,12,89,0]]
christofides.compute(distance_matrix) returns a Dictionary with following Keys:

Christofides_Solution, Travel_Cost, MST, Odd_Vertices Indexes, Multigraph, Euler_Tour

• Christofides_Solution: A list consisting of approximate tour for TSP.

Use: TSP[‘Chistofides_Solution’]

• Travel_Cost: The cost of TSP tour generated.

Use: TSP[‘Travel_Cost’]

• MST: The minimum spanning tree generated during the Christofides algorithm.

Use: TSP[‘MST’]

• Odd_Vertices: A list of odd vertices of minimum spanning tree.

Use: TSP[‘Odd_Vertices’]

• Indexes: List of edges from minimum cost perfect matching of odd vertices.

Use: TSP[‘Indexes’]

• Multigraph: Edges of multigraph formed after Indexing.

Use: TSP[‘Multigraph’]

• Euler_Tour: The Euler Tour of the Multigraph.

Use: TSP[‘Euler_Tour’]

## Support Functions in christofides

• _csr_gen_triples(csr_matrix)

• _odd_vertices_of_MST(distance_matrix, number_of_nodes)

• min_Munkres(distance_matrix, bipartitie_graphs)

• Munkres_cost(indexes, bipartite_graph)

• bipartite_Graph(distance_matrix, bipartite_set, odd_vertices)

• create_Multigraph(distance_matrix, MST, indexes, odd_vertices)

• Euler_Tour(multigraph)

• shortcut_Euler_Tour(tour)

• cost(christofides_tour, distance_matrix)

## Install

python setup.py install

scipy, numpy, networkx, munkres

## Project details

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