feat: Add travelling salesman problem(Naive Approach)

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Mayank17M
2021-09-07 12:30:10 +05:30
parent 1e8b4a754a
commit 9d0f817563

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@@ -1,50 +1,108 @@
// Travelling salesman problem states that:
// Given a list of cities and the distances between each pair of cities, what is
// the shortest possible route that visits each city exactly once and returns to
// the origin city?
// This is the naive approach to solve this problem.
/**
* @file
* @brief [Travelling Salesman Problem]
* (https://en.wikipedia.org/wiki/Travelling_salesman_problem)
*
* @author [Mayank Mamgain](http://github.com/Mayank17M)
*
* @details
* Travelling salesman problem asks:
* Given a list of cities and the distances between each pair of cities, what is
* the shortest possible route that visits each city exactly once and returns to
* the origin city?
* TSP can be modelled as an undirected weighted graph, such that cities are the
* graph's vertices, paths are the graph's edges, and a path's distance is the
* edge's weight. It is a minimization problem starting and finishing at a
* specified vertex after having visited each other vertex exactly once.
* This is the naive implementation of the problem.
*/
// References:
// https://en.wikipedia.org/wiki/Travelling_salesman_problem
#include <limits.h>
#include <algorithm>
#include <cassert>
#include <iostream>
#include <vector>
using namespace std;
int TravellingSalesmanProblem(vector<vector<int>> cities, int src, int V) {
vector<int> vtx;
/**
* @namespace graph
* @brief Graph Algorithms
*/
namespace graph {
/**
* @brief Function calculates the minimum path distance that will cover all the
* cities starting from the source.
*
* @param cities matrix representation of cities
* @param src Point from where salesman is starting
* @param V number of vertices in the graph
*
*/
int TravellingSalesmanProblem(std::vector<std::vector<int>> *cities, int src,
int V) {
//// vtx stores the vertexs of the graph
std::vector<int> vtx;
for (int i = 0; i < V; i++) {
if (i != src) {
vtx.push_back(i);
}
}
// store minimum weight Hamiltonian Cycle.
//// store minimum weight Hamiltonian Cycle.
int min_path = INT_MAX;
do {
// store current Path weight(cost)
//// store current Path weight(cost)
int curr_weight = 0;
// compute current path weight
//// compute current path weight
int k = src;
for (int i = 0; i < vtx.size(); i++) {
curr_weight += cities[k][vtx[i]];
for (auto i = 0U; i < vtx.size(); i++) {
curr_weight += (*cities)[k][vtx[i]];
k = vtx[i];
}
curr_weight += cities[k][src];
curr_weight += (*cities)[k][src];
// update minimum
min_path = min(min_path, curr_weight);
//// update minimum
min_path = std::min(min_path, curr_weight);
} while (next_permutation(vtx.begin(), vtx.end()));
return min_path;
}
} // namespace graph
int main() {
vector<vector<int>> cities = {
/** Function to test the Algorithm */
void tests() {
std::cout << "Initiatinig Predefined Tests..." << std::endl;
std::cout << "Initiating Test 1..." << std::endl;
std::vector<std::vector<int>> cities = {
{0, 20, 42, 35}, {20, 0, 30, 34}, {42, 30, 0, 12}, {35, 34, 12, 0}};
int V = cities.size();
cout << TravellingSalesmanProblem(cities, 0, V);
assert(graph::TravellingSalesmanProblem(&cities, 0, V) == 97);
std::cout << "Test 1 Passed..." << std::endl;
std::cout << "Initiating Test 2..." << std::endl;
cities = {{0, 5, 10, 15}, {5, 0, 20, 30}, {10, 20, 0, 35}, {15, 30, 35, 0}};
V = cities.size();
assert(graph::TravellingSalesmanProblem(&cities, 0, V) == 75);
std::cout << "Test 2 Passed..." << std::endl;
std::cout << "Initiating Test 3..." << std::endl;
cities = {
{0, 10, 15, 20}, {10, 0, 35, 25}, {15, 35, 0, 30}, {20, 25, 30, 0}};
V = cities.size();
assert(graph::TravellingSalesmanProblem(&cities, 0, V) == 80);
std::cout << "Test 3 Passed..." << std::endl;
}
/** Main function */
int main() {
tests();
std::vector<std::vector<int>> cities = {
{0, 5, 10, 15}, {5, 0, 20, 30}, {10, 20, 0, 35}, {15, 30, 35, 0}};
int V = cities.size();
std::cout << graph::TravellingSalesmanProblem(&cities, 0, V);
}