From 1b41ac0810bb524ef16e61e774e58d1544d6ea10 Mon Sep 17 00:00:00 2001
From: Manu Gond <manugond45@gmail.com>
Date: Tue, 7 Aug 2018 10:38:52 +0530
Subject: [PATCH] initial commit

---
 TSP.cpp                                  | 310 +++++++++++++++++++++
 TSP_Input_2                              |  49 ++++
 TSP_Output                               | 208 ++++++++++++++
 TSPusingGAwithRouletteWhellSelection.cpp | 330 +++++++++++++++++++++++
 4 files changed, 897 insertions(+)
 create mode 100644 TSP.cpp
 create mode 100644 TSP_Input_2
 create mode 100644 TSP_Output
 create mode 100644 TSPusingGAwithRouletteWhellSelection.cpp

diff --git a/TSP.cpp b/TSP.cpp
new file mode 100644
index 0000000..a2dfdf3
--- /dev/null
+++ b/TSP.cpp
@@ -0,0 +1,310 @@
+#include<iostream>
+#include<vector>
+#include<algorithm>
+#include<stdint.h>
+#include<string.h>
+#include<random>
+#define random (rand()/(double)RAND_MAX)
+#define ll int64_t
+#define Add push_back
+using namespace std;
+//=======================================================================//
+//=====================Class Definition of Graph=========================//
+//=======================================================================//
+class Graph{
+	ll TotalVertices;
+	vector<pair<ll,ll> >Vertices; //pair of vertices between which path exists
+	vector<pair<ll,ll> >Edges; //first one is weight and second one is index corresponding to the vertex pair
+	vector<ll>OptimalPath;		//this will store the path for which TotalCost variable's value will be set
+	ll TotalCost;
+public:
+	Graph(ll TotalVertices){
+		TotalCost=0;
+		this->TotalVertices=TotalVertices;	
+	}
+	Graph(){				//Add entries for the vertice and edges, addEdge(Vertex1,Vertex2,WeightOfEdge)
+		this->TotalVertices=5;
+		addEdge(1,2,7);
+		addEdge(1,3,50);
+		addEdge(1,4,6);
+		addEdge(1,5,4);
+		addEdge(2,3,11);
+		addEdge(2,4,5);
+		addEdge(2,5,15);
+		addEdge(3,4,8);
+		addEdge(3,5,2);
+		addEdge(4,5,27);
+	}
+	void addEdge(ll v1,ll v2,ll weight);	//given verices and edge weight betwene them, add a new entry into graph
+	void display(void);						//display the current graph contents
+	ll getCost(vector<ll>Path);				//give a path funciton will reutrn the travel cost or 0 in case path is not valid
+	ll getCost();							//in case the optimal path is set then return the cost of that path
+	ll getTotalVertices();					//return total number of vertices in the Graph
+	bool isPathValid(vector<ll>Path);		//for checking is path is valid
+	void setPath(vector<ll>OptimalPath);	//set the current optimal path as received from the calling function
+	ll getDecesionVariables();				//return the number of decesion variables, TotalVertices in this case;
+};
+//===========================================================//
+//===================Class definition of Individual==========//
+//===========================================================//
+class Individual{
+	vector<ll>Gene;							//Gene will hold the path 
+	ll DecesionVariables;					//Total number of vertices in this case
+	Graph Properties;						//An ofject of Graph type to calculate the path cost and find validity of an randomly choosen path
+public:
+	Individual(){
+		Properties=Graph();					//Create a Graph type object
+		DecesionVariables=Properties.getDecesionVariables();
+		Gene.resize(DecesionVariables,0);	//Resize the Gene array to the size of TotalVertices and initialize them with 0
+		do{
+			Gene.clear();					
+			Gene.resize(DecesionVariables,0);	
+			for(ll i=0;i<Gene.size();i++){
+				ll vertex=(random*DecesionVariables)+1;
+				while(find(Gene.begin(),Gene.end(),vertex)!=Gene.end()){  //if randomly created vertex is already added in Gene then create a new one
+					vertex=(random*DecesionVariables)+1;
+				}
+				Gene[i]=vertex;			//add created valid vertex into the Gene
+			}							 
+		}while(!Properties.isPathValid(Gene));	//check if the created path is valid
+		Properties.setPath(Gene);				//if path(Gene) is valid then set this path as the optimal path for the Graph object
+		this->Fitness=Properties.getCost();		//get the cost of path form the Graph object corresponding to this individual's Gene
+	}
+	ll Fitness;									
+	ll getFitness();							
+	vector<ll>getGene();						//return the Gene array 
+	bool isGeneValid(vector<ll>Array);			//given an array of path check if it is valid path or not
+	void setGene(vector<ll>Gene);				//set the Gene of this individual equal to the received path array
+	void displayIndividual();
+	ll getDecesionVariables();
+};
+bool compare(const Individual & l,const Individual & r){	//this compartor function is required for 'sort()' function defined in <algorithm>
+    return l.Fitness < r.Fitness;							//for sorting objects according to one of their data members (Cost/Fitness in this case)
+}
+//===========================================================//
+//===================Class definition of SimulateGA==========//
+//===========================================================//
+class SimulateGA{
+	vector<Individual>Population;				//List of population
+	ll PopulationSize;							//Initial population size (as for now in this program this must be even)
+public:
+	SimulateGA(int PopulationSize){
+		this->PopulationSize=PopulationSize;	//Initialize the population with given size 
+		Population.resize(PopulationSize);		//Resize the population array to the Population size
+	}
+	void doCrossover();							
+	vector<ll> doMutation(vector<ll>Array);		//Mutation on the passed array of genes
+	void displayPopulation();					
+	void displayFittest();
+};
+//===========================================================//
+//==============Member functions for SimulateGA Class========//
+//===========================================================//
+void SimulateGA::displayPopulation(){
+	for(int i=0;i<Population.size();i++){
+		cout<<endl;
+		Population[i].displayIndividual();
+	}
+}
+void SimulateGA::displayFittest(){
+	cout<<"\nFittest Individual: \n";
+	(*min_element(Population.begin(),Population.end(),compare)).displayIndividual();//display the best cost(Min fitness value in this case) individual
+}
+void SimulateGA::doCrossover(){
+	vector<Individual>NewPopulation;
+	ll range=Population[0].getDecesionVariables();
+	vector<pair<ll,ll> >MatingPair;
+	for(ll i=0;i<PopulationSize/2;i++){	//create the mating pair from while population by randomly selecting them
+		ll p1=random*PopulationSize;
+		ll p2=random*PopulationSize;
+		MatingPair.Add(make_pair(p1,p2));
+	}
+	//select mating pair in best to worst order 
+	/*sort(Population.begin(),Population.end(),compare);	//sort the population so the fittest ones will be at top
+	for(ll i=0;i<PopulationSize/2;i++){	//create the mating pair from while population
+		ll p1=i;	//select the most fit ones to be added in mating pair
+		ll p2=i+1;
+		MatingPair.Add(make_pair(p1,p2));
+	}*/
+	for(ll index=0;index<MatingPair.size();index++){
+		Individual Parent1=Population[MatingPair[index].first];		//Select 1st parent from population as per mating pair 
+		Individual Parent2=Population[MatingPair[index].second];	//Select 2nd parent from population as per mating pair 
+		vector<ll>Gene1=Parent1.getGene();							//Obtain genes of first parent
+		vector<ll>Gene2=Parent2.getGene();							//Obtain genes of the second parent
+		vector<ll>Points;											
+		Points.Add(random*Gene1.size());							//select two random points
+		Points.Add(random*Gene2.size());
+		sort(Points.begin(),Points.end());							//sort the random points so that they can be used as a range for swapping
+		vector<ll>ChildGene1(range);
+		vector<ll>ChildGene2(range);
+		for(ll i=Points[0];i<Points[1];i++){						//add the genes of parents within the selected range
+			ChildGene1[i]=Gene1[i];
+			ChildGene2[i]=Gene2[i];
+		}
+		for(ll i=0;i<range;i++){									//add remaining genes in such a way that no two verties are repeated
+			if(ChildGene1[i]==0){
+				ll id=0;
+				ll flag=0;
+				do{
+					if(find(ChildGene1.begin(),ChildGene1.end(),Gene2[id])==ChildGene1.end()){
+						ChildGene1[i]=Gene1[id];
+						flag=1;
+					}
+					id++;
+				}while(flag==0);
+			}
+			if(ChildGene2[i]==0){
+				ll id=0;
+				ll flag=0;
+				do{
+					if(find(ChildGene2.begin(),ChildGene2.end(),Gene1[id])==ChildGene2.end()){
+						ChildGene1[i]=Gene1[id];
+						flag=1;
+					}
+					id++;
+				}while(flag==0);
+			}
+		}
+		ChildGene1=doMutation(ChildGene1);				//do mutaiton on this gene array of both childs
+		ChildGene2=doMutation(ChildGene2);
+		vector<Individual>Family;
+		Family.Add(Parent1);						//add both parnets to family list 
+		Family.Add(Parent2);
+		Individual Child1;
+		Individual Child2;
+		if(Child1.isGeneValid(ChildGene1)){			//add children if they have valid gene
+			Child1.setGene(ChildGene1);
+			Family.Add(Child1);
+		}
+		if(Child1.isGeneValid(ChildGene2)){
+			Child1.setGene(ChildGene2);
+			Family.Add(Child2);
+		}
+		sort(Family.begin(),Family.end(),compare);	//sort the family based on their fitness (lower fitness here in this case because of minimization problem)
+		NewPopulation.Add(Family[0]);		//select top 2 individual whether its parent or child and add them into new list of population
+		NewPopulation.Add(Family[1]);
+	}
+	Population.clear();
+	Population=NewPopulation;		//replace the current population with new population 
+}
+vector<ll> SimulateGA::doMutation(vector<ll>Array){
+	Individual Person;
+	ll r1=random*Array.size();
+	ll r2=random*Array.size();
+	vector<ll>Temp=Array;
+	Temp=Array;
+	ll t=Temp[r1];
+	Temp[r1]=Temp[r2];
+	Temp[r2]=t;
+	return Temp;
+}
+//===========================================================//
+//==============Member functions for Individual Class========//
+//===========================================================//
+ll Individual::getFitness(){
+	return Fitness;
+}
+vector<ll> Individual::getGene(){
+	return Gene;
+}
+bool Individual::isGeneValid(vector<ll>Array){
+	if(Properties.isPathValid(Array)){
+		return true;
+	}
+	return false;
+}
+void Individual::setGene(vector<ll>Gene){
+	this->Gene=Gene;
+	Properties.setPath(Gene);
+	this->Fitness=Properties.getCost();
+}
+void Individual::displayIndividual(){
+	cout<<"Path: ";
+	for(int i=0;i<Gene.size();i++){
+		cout<<Gene[i]<<" ";
+	}
+	cout<<"Fitness: "<<Fitness;
+}
+ll Individual::getDecesionVariables(){
+	return this->DecesionVariables;
+}
+//===========================================================//
+//================Member functions for Graph Class===========//
+//===========================================================//
+bool Graph::isPathValid(vector<ll>Path){
+	if(getCost(Path)==0){
+		return false;
+	}
+	return true;
+}
+void Graph::addEdge(ll v1,ll v2,ll weight){
+	Vertices.Add(make_pair(v1,v2));
+	Edges.Add(make_pair(weight,Vertices.size()-1));
+}
+void Graph::display(void){
+	cout<<"\nGraph Contents: \n";
+	for(int i=0;i<Edges.size();i++){
+		cout<<"Vertex: "<<Vertices[i].first<<" Vertex: "<<Vertices[i].second<<" Edge: "<<Edges[i].first<<endl;
+	}
+}
+ll Graph::getCost(vector<ll>Path){
+	ll cost=0;
+	vector<ll>visited;
+	for(ll i=0;i<Path.size()-1;i++){
+		ll v1=Path[i];
+		ll v2=Path[i+1];
+		if(find(visited.begin(),visited.end(),v1)==visited.end()){
+			visited.Add(v1);
+		}
+		else{
+			return 0;
+		}
+		if(i==Path.size()-2){
+			if(find(visited.begin(),visited.end(),v2)==visited.end()){
+			visited.Add(v2);
+			}
+			else{
+				return 0;
+			}
+		}
+		if(find(Vertices.begin(),Vertices.end(),make_pair(v1,v2))<Vertices.end()){
+			cost+=Edges[(find(Vertices.begin(),Vertices.end(),make_pair(v1,v2))-Vertices.begin())].first;
+		}
+		else if(find(Vertices.begin(),Vertices.end(),make_pair(v2,v1))<Vertices.end()){
+			cost+=Edges[(find(Vertices.begin(),Vertices.end(),make_pair(v2,v1))-Vertices.begin())].first;
+		}
+		else{
+			//cout<<"\nNo path found! ";
+			return 0;
+		}
+	}
+	return cost;
+}
+ll Graph::getTotalVertices(){
+	return TotalVertices;	
+}
+void Graph::setPath(vector<ll>OptimalPath){
+	this->OptimalPath=OptimalPath;
+	TotalCost=getCost(OptimalPath);
+}
+ll Graph::getCost(){
+	return TotalCost;
+}
+ll Graph::getDecesionVariables(){
+	return TotalVertices;
+}
+int main(){
+	SimulateGA g=SimulateGA(100);
+	cout<<"\n==================Initial Population==============\n";
+	//g.displayPopulation();
+	g.displayFittest();
+	for(int i=0;i<10;i++){
+	cout<<"\n==================Generation "<<i+1<<"==============\n";
+	g.doCrossover();
+	//g.displayPopulation();
+	g.displayFittest();
+	}
+	//g.displayPopulation();
+	g.displayFittest();
+	return 0;
+}
diff --git a/TSP_Input_2 b/TSP_Input_2
new file mode 100644
index 0000000..db6b53d
--- /dev/null
+++ b/TSP_Input_2
@@ -0,0 +1,49 @@
+Graph(){
+		this->TotalVertices=17;
+		addEdge(1,2,633);addEdge(1,3,257);addEdge(1,4,91);addEdge(1,5,412);addEdge(1,6,150);addEdge(1,7,80);addEdge(1,8,134);addEdge(1,9,259);
+		addEdge(1,10,505);addEdge(1,11,353);addEdge(1,12,324);addEdge(1,13,70);addEdge(1,14,211);addEdge(1,15,268);addEdge(1,16,246);addEdge(1,17,121);
+		//=================================================================================================================//
+		addEdge(2,3,390);addEdge(2,4,661);addEdge(2,5,227);addEdge(2,6,488);addEdge(2,7,572);addEdge(2,8,530);addEdge(2,9,555);addEdge(2,10,289);
+		addEdge(2,11,282);addEdge(2,12,638);addEdge(2,13,567);addEdge(2,14,466);addEdge(2,15,420);addEdge(2,16,745);addEdge(2,17,518);
+		//=================================================================================================================//
+		addEdge(3,4,228);addEdge(3,5,169);addEdge(3,6,112);addEdge(3,7,196);addEdge(3,8,154);addEdge(3,9,372);addEdge(3,10,262);
+		addEdge(3,11,110);addEdge(3,12,437);addEdge(3,13,191);addEdge(3,14,74);addEdge(3,15,53);addEdge(3,16,472);addEdge(3,17,142);
+		//=================================================================================================================//
+		addEdge(4,5,383);addEdge(4,6,120);addEdge(4,7,77);addEdge(4,8,105);addEdge(4,9,175);addEdge(4,10,476);addEdge(4,11,324);
+		addEdge(4,12,240);addEdge(4,13,27);addEdge(4,14,182);addEdge(4,15,239);addEdge(4,16,237);addEdge(4,17,84);
+		//=================================================================================================================//
+		addEdge(5,6,267);addEdge(5,7,351);addEdge(5,8,309);addEdge(5,9,338);addEdge(5,10,196);addEdge(5,11,61);
+		addEdge(5,12,421);addEdge(5,13,346);addEdge(5,14,243);addEdge(5,15,199);addEdge(5,16,528);addEdge(5,17,297);
+		//=================================================================================================================//
+		addEdge(6,7,63);addEdge(6,8,34);addEdge(6,9,264);addEdge(6,10,360);addEdge(6,11,208);addEdge(6,12,329);
+		addEdge(6,13,83);addEdge(6,14,105);addEdge(6,15,123);addEdge(6,16,364);addEdge(6,17,35);
+		//=================================================================================================================//
+		addEdge(7,8,29);addEdge(7,9,232);addEdge(7,10,444);addEdge(7,11,292);addEdge(7,12,297);
+		addEdge(7,13,47);addEdge(7,14,150);addEdge(7,15,207);addEdge(7,16,332);addEdge(7,17,29);
+		//=================================================================================================================//
+		addEdge(8,9,249);addEdge(8,10,402);addEdge(8,11,250);addEdge(8,12,314);addEdge(8,13,68);
+		addEdge(8,14,108);addEdge(8,15,165);addEdge(8,16,349);addEdge(8,17,36);
+		//=================================================================================================================//
+		addEdge(9,10,495);addEdge(9,11,352);addEdge(9,12,95);addEdge(9,13,189);
+		addEdge(9,14,326);addEdge(9,15,383);addEdge(9,16,202);addEdge(9,17,236);
+		//=================================================================================================================//
+		addEdge(10,11,154);addEdge(10,12,578);addEdge(10,13,439);addEdge(10,14,336);
+		addEdge(10,15,240);addEdge(10,16,685);addEdge(10,17,390);
+		//=================================================================================================================//
+		addEdge(11,12,435);addEdge(11,13,287);addEdge(11,14,184);
+		addEdge(11,15,140);addEdge(11,16,542);addEdge(11,17,238);
+		//=================================================================================================================//
+		addEdge(12,13,254);addEdge(12,14,391);addEdge(12,15,448);
+		addEdge(12,16,157);addEdge(12,17,301);
+		//=================================================================================================================//
+		addEdge(13,14,145);addEdge(13,15,202);
+		addEdge(13,16,289);addEdge(13,17,55);
+		//=================================================================================================================//
+		addEdge(14,15,57);addEdge(14,16,426);
+		addEdge(14,17,96);
+		//=================================================================================================================//
+		addEdge(15,16,483);
+		addEdge(15,17,153);
+		//=================================================================================================================//
+		addEdge(16,17,336);
+	}
\ No newline at end of file
diff --git a/TSP_Output b/TSP_Output
new file mode 100644
index 0000000..33f21a1
--- /dev/null
+++ b/TSP_Output
@@ -0,0 +1,208 @@
+==================Initial Population==============
+
+Fittest Individual:
+Path: 3 2 4 1 5 Fitness: 26
+==================Generation 1==============
+
+Fittest Individual:
+Path: 3 5 4 2 1 Fitness: 41
+==================Generation 2==============
+
+Fittest Individual:
+Path: 3 5 4 2 1 Fitness: 41
+==================Generation 3==============
+
+Fittest Individual:
+Path: 3 5 4 2 1 Fitness: 41
+==================Generation 4==============
+
+Fittest Individual:
+Path: 3 5 4 2 1 Fitness: 41
+==================Generation 5==============
+
+Fittest Individual:
+Path: 3 5 4 2 1 Fitness: 41
+==================Generation 6==============
+
+Fittest Individual:
+Path: 3 5 4 2 1 Fitness: 41
+==================Generation 7==============
+
+Fittest Individual:
+Path: 3 5 4 2 1 Fitness: 41
+==================Generation 8==============
+
+Fittest Individual:
+Path: 1 5 4 3 2 Fitness: 50
+==================Generation 9==============
+
+Fittest Individual:
+Path: 1 5 4 3 2 Fitness: 50
+==================Generation 10==============
+
+Fittest Individual:
+Path: 1 5 4 3 2 Fitness: 50
+==================Generation 11==============
+
+Fittest Individual:
+Path: 1 5 4 3 2 Fitness: 50
+==================Generation 12==============
+
+Fittest Individual:
+Path: 1 5 4 3 2 Fitness: 50
+==================Generation 13==============
+
+Fittest Individual:
+Path: 3 2 5 1 4 Fitness: 36
+==================Generation 14==============
+
+Fittest Individual:
+Path: 3 2 5 1 4 Fitness: 36
+==================Generation 15==============
+
+Fittest Individual:
+Path: 3 2 5 1 4 Fitness: 36
+==================Generation 16==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 17==============
+
+Fittest Individual:
+Path: 1 2 5 3 4 Fitness: 32
+==================Generation 18==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 19==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 20==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 21==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 22==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 23==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 24==============
+
+Fittest Individual:
+Path: 3 4 5 2 1 Fitness: 57
+==================Generation 25==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 26==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 27==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 28==============
+
+Fittest Individual:
+Path: 3 2 5 4 1 Fitness: 59
+==================Generation 29==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 30==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 31==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 32==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 33==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 34==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 35==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 36==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 37==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 38==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 39==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 40==============
+
+Fittest Individual:
+Path: 5 3 1 2 4 Fitness: 64
+==================Generation 41==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+==================Generation 42==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+==================Generation 43==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+==================Generation 44==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+==================Generation 45==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+==================Generation 46==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+==================Generation 47==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+==================Generation 48==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+==================Generation 49==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+==================Generation 50==============
+
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+Fittest Individual:
+Path: 5 3 4 2 1 Fitness: 22
+--------------------------------
+Process exited after 0.8932 seconds with return value 0
\ No newline at end of file
diff --git a/TSPusingGAwithRouletteWhellSelection.cpp b/TSPusingGAwithRouletteWhellSelection.cpp
new file mode 100644
index 0000000..81ef194
--- /dev/null
+++ b/TSPusingGAwithRouletteWhellSelection.cpp
@@ -0,0 +1,330 @@
+#include<iostream>
+#include<vector>
+#include<algorithm>
+#include<stdint.h>
+#include<string.h>
+#include<random>
+#define random (rand()/(double)RAND_MAX)
+#define ll int64_t
+#define Add push_back
+using namespace std;
+//=======================================================================//
+//=====================Class Definition of Graph=========================//
+//=======================================================================//
+class Graph{
+	ll TotalVertices;
+	vector<pair<ll,ll> >Vertices; //pair of vertices between which path exists
+	vector<pair<ll,ll> >Edges; //first one is weight and second one is index corresponding to the vertex pair
+	vector<ll>OptimalPath;
+	ll TotalCost;
+public:
+	Graph(ll TotalVertices){
+		TotalCost=0;
+		this->TotalVertices=TotalVertices;
+	}
+	Graph(){
+		this->TotalVertices=5;
+		addEdge(1,2,7);
+		addEdge(1,3,50);
+		addEdge(1,4,6);
+		addEdge(1,5,4);
+		addEdge(2,3,11);
+		addEdge(2,4,5);
+		addEdge(2,5,15);
+		addEdge(3,4,8);
+		addEdge(3,5,2);
+		addEdge(4,5,27);
+	}
+	void addAll(vector<pair<ll,ll> >Vertices,vector<pair<ll,ll> >Edges);
+	void addEdge(ll v1,ll v2,ll weight);	//given verices and edge weight betwene them, add a new entry into graph
+	void display(void);						//display the current graph contents
+	ll getCost(vector<ll>Path);				//give a path funciton will reutrn the travel cost or 0 in case path is not valid
+	ll getCost();							//in case the optimal path is set then return the cost of that path
+	ll getTotalVertices();					//return total number of vertices in the Graph
+	bool isPathValid(vector<ll>Path);		//for checking is path is valid
+	void setPath(vector<ll>OptimalPath);	//set the current optimal path as received from the calling function
+	ll getDecesionVariables();
+};
+//===========================================================//
+//===================Class definition of Individual==========//
+//===========================================================//
+class Individual{
+	vector<ll>Gene;
+	ll DecesionVariables;
+	Graph Properties;
+public:
+	Individual(){
+		Properties=Graph();
+		DecesionVariables=Properties.getDecesionVariables();
+		Gene.resize(DecesionVariables,0);
+		do{
+			Gene.clear();
+			Gene.resize(DecesionVariables,0);
+			for(ll i=0;i<Gene.size();i++){
+				ll vertex=(random*DecesionVariables)+1;
+				while(find(Gene.begin(),Gene.end(),vertex)!=Gene.end()){
+					vertex=(random*DecesionVariables)+1;
+				}
+				Gene[i]=vertex;			}
+		}while(!Properties.isPathValid(Gene));
+		Properties.setPath(Gene);
+		this->Fitness=Properties.getCost();
+	}
+	ll Fitness;
+	ll getFitness();
+	vector<ll>getGene();
+	bool isGeneValid(vector<ll>Array);
+	void setGene(vector<ll>Gene);
+	void displayIndividual();
+	ll getDecesionVariables();
+};
+bool compare(const Individual & l,const Individual & r)
+{
+    return l.Fitness < r.Fitness;
+}
+//===========================================================//
+//===================Class definition of SimulateGA==========//
+//===========================================================//
+class SimulateGA{
+	vector<Individual>Population;
+	ll PopulationSize;
+public:
+	SimulateGA(int PopulationSize){
+		this->PopulationSize=PopulationSize;
+		Population.resize(PopulationSize);
+	}
+	void doCrossover();
+	vector<ll> doMutation(vector<ll>Array);
+	void displayPopulation();
+	void displayFittest();
+	vector<pair<ll,ll> > RouletteWheelSelection();
+};
+//===========================================================//
+//==============Member functions for SimulateGA Class========//
+//===========================================================//
+void SimulateGA::displayPopulation(){
+	for(int i=0;i<Population.size();i++){
+		cout<<endl;
+		Population[i].displayIndividual();
+	}
+}
+void SimulateGA::displayFittest(){
+	(*min_element(Population.begin(),Population.end(),compare)).displayIndividual();
+}
+vector<pair<ll,ll> > SimulateGA::RouletteWheelSelection(){
+	vector<pair<ll,ll> >MatingPair;
+	ll SumFitness=0;
+	for(ll i=0;i<PopulationSize;i++){
+		SumFitness+=Population[i].getFitness();
+	}
+	for(ll i=0;i<PopulationSize/2;i++){
+		ll r=random*SumFitness;
+		ll Sum=0;
+		ll j=0;
+		while(Sum<r){
+			Sum+=Population[j].getFitness();
+			j++;
+		}
+		ll pair1=--j;
+		r=random*SumFitness;
+		Sum=0;
+		j=0;
+		while(Sum<r){
+			Sum+=Population[j].getFitness();
+			j++;
+		}
+		ll pair2=--j;
+		MatingPair.Add(make_pair(pair1,pair2));
+	}
+	return MatingPair;
+}
+void SimulateGA::doCrossover(){
+	vector<Individual>NewPopulation;
+	ll range=Population[0].getDecesionVariables();
+	vector<pair<ll,ll> >MatingPair;
+	MatingPair=RouletteWheelSelection(); //call Roulette Wheel Selection function to select the mating pairs
+	for(ll index=0;index<MatingPair.size();index++){
+		Individual Parent1=Population[MatingPair[index].first];
+		Individual Parent2=Population[MatingPair[index].second];
+		vector<ll>Gene1=Parent1.getGene();
+		vector<ll>Gene2=Parent2.getGene();
+		vector<ll>Points;
+		Points.Add(random*Gene1.size());
+		Points.Add(random*Gene2.size());
+		sort(Points.begin(),Points.end());
+		vector<ll>ChildGene1(range);
+		vector<ll>ChildGene2(range);
+		for(ll i=Points[0];i<Points[1];i++){
+			ChildGene1[i]=Gene1[i];
+			ChildGene2[i]=Gene2[i];
+		}
+		for(ll i=0;i<range;i++){
+			if(ChildGene1[i]==0){
+				ll id=0;
+				ll flag=0;
+				do{
+					if(find(ChildGene1.begin(),ChildGene1.end(),Gene2[id])==ChildGene1.end()){
+						ChildGene1[i]=Gene1[id];
+						flag=1;
+					}
+					id++;
+				}while(flag==0);
+			}
+			if(ChildGene2[i]==0){
+				ll id=0;
+				ll flag=0;
+				do{
+					if(find(ChildGene2.begin(),ChildGene2.end(),Gene1[id])==ChildGene2.end()){
+						ChildGene1[i]=Gene1[id];
+						flag=1;
+					}
+					id++;
+				}while(flag==0);
+			}
+		}
+		ChildGene1=doMutation(ChildGene1);
+		ChildGene2=doMutation(ChildGene2);
+		vector<Individual>Family;
+		Family.Add(Parent1);
+		Family.Add(Parent2);
+		Individual Child1;
+		Individual Child2;
+		if(Child1.isGeneValid(ChildGene1)){
+			Child1.setGene(ChildGene1);
+			Family.Add(Child1);
+		}
+		if(Child1.isGeneValid(ChildGene2)){
+			Child1.setGene(ChildGene2);
+			Family.Add(Child2);
+		}
+		sort(Family.begin(),Family.end(),compare);
+		NewPopulation.Add(Family[0]);
+		NewPopulation.Add(Family[1]);
+	}
+	Population.clear();
+	Population=NewPopulation;
+}
+vector<ll> SimulateGA::doMutation(vector<ll>Array){
+	Individual Person;
+	ll r1=random*Array.size();
+	ll r2=random*Array.size();
+	vector<ll>Temp=Array;
+	Temp=Array;
+	ll t=Temp[r1];
+	Temp[r1]=Temp[r2];
+	Temp[r2]=t;
+	return Temp;
+}
+//===========================================================//
+//==============Member functions for Individual Class========//
+//===========================================================//
+ll Individual::getFitness(){
+	return Fitness;
+}
+vector<ll> Individual::getGene(){
+	return Gene;
+}
+bool Individual::isGeneValid(vector<ll>Array){
+	if(Properties.isPathValid(Array)){
+		return true;
+	}
+	return false;
+}
+void Individual::setGene(vector<ll>Gene){
+	this->Gene=Gene;
+	Properties.setPath(Gene);
+	this->Fitness=Properties.getCost();
+}
+void Individual::displayIndividual(){
+	cout<<"Path: ";
+	for(int i=0;i<Gene.size();i++){
+		cout<<Gene[i]<<" ";
+	}
+	cout<<"Fitness: "<<Fitness;
+}
+ll Individual::getDecesionVariables(){
+	return this->DecesionVariables;
+}
+//===========================================================//
+//================Member functions for Graph Class===========//
+//===========================================================//
+bool Graph::isPathValid(vector<ll>Path){
+	if(getCost(Path)==0){
+		return false;
+	}
+	return true;
+}
+void Graph::addAll(vector<pair<ll,ll> >Vertices,vector<pair<ll,ll> >Edges){
+	this->Vertices=Vertices;
+	this->Edges=Edges;
+}
+void Graph::addEdge(ll v1,ll v2,ll weight){
+	Vertices.Add(make_pair(v1,v2));
+	Edges.Add(make_pair(weight,Vertices.size()-1));
+}
+void Graph::display(void){
+	cout<<"\nGraph Contents: \n";
+	for(int i=0;i<Edges.size();i++){
+		cout<<"Vertex: "<<Vertices[i].first<<" Vertex: "<<Vertices[i].second<<" Edge: "<<Edges[i].first<<endl;
+	}
+}
+ll Graph::getTotalVertices(){
+	return TotalVertices;	
+}
+void Graph::setPath(vector<ll>OptimalPath){
+	this->OptimalPath=OptimalPath;
+	TotalCost=getCost(OptimalPath);
+}
+ll Graph::getCost(){
+	return TotalCost;
+}
+ll Graph::getCost(vector<ll>Path){
+	ll cost=0;
+	vector<ll>visited;
+	for(ll i=0;i<Path.size()-1;i++){
+		ll v1=Path[i];
+		ll v2=Path[i+1];
+		if(find(visited.begin(),visited.end(),v1)==visited.end()){
+			visited.Add(v1);
+		}
+		else{
+			return 0;
+		}
+		if(i==Path.size()-2){
+			if(find(visited.begin(),visited.end(),v2)==visited.end()){
+			visited.Add(v2);
+			}
+			else{
+				return 0;
+			}
+		}
+		if(find(Vertices.begin(),Vertices.end(),make_pair(v1,v2))<Vertices.end()){
+			cost+=Edges[(find(Vertices.begin(),Vertices.end(),make_pair(v1,v2))-Vertices.begin())].first;
+		}
+		else if(find(Vertices.begin(),Vertices.end(),make_pair(v2,v1))<Vertices.end()){
+			cost+=Edges[(find(Vertices.begin(),Vertices.end(),make_pair(v2,v1))-Vertices.begin())].first;
+		}
+		else{
+			//cout<<"\nNo path found! ";
+			return 0;
+		}
+	}
+	return cost;
+}
+ll Graph::getDecesionVariables(){
+	return TotalVertices;
+}
+int main(){
+	SimulateGA g=SimulateGA(100);
+	cout<<"\n==================Initial Population==============\n";
+	//g.displayPopulation();
+	g.displayFittest();
+	for(int i=0;i<10;i++){
+		cout<<"\n==================Generation "<<i+1<<"==============\n";
+		g.doCrossover();
+		g.displayFittest();
+	}
+	//g.displayPopulation();
+	g.displayFittest();
+	return 0;
+}