Merge pull request #90 from raj-rathod/rajesh

feat:<Greedy Algorithm> greedy algorithm content set

Author: raj-rathod

src/app/components/Algorithms/greedy/greedy-algorithm/greedy-algorithm.component.html

@@ -1 +1,9 @@
-<p class="text-center mt-5">Coming soon</p>
+<h1 class="text-center">Greedy Algorithm</h1>
+<div class="mt-md-4 mt-3" [innerHtml]="greedyMetaData.defination"></div>
+<div class="mt-md-4 mt-3" [innerHtml]="greedyMetaData.example"></div>
+<div class="mt-md-4 mt-3" [innerHtml]="greedyMetaData.properties"></div>
+<div class="mt-md-4 mt-3" [innerHtml]="greedyMetaData.components"></div>
+<div class="mt-md-4 mt-3" [innerHtml]="greedyMetaData.algorithm"></div>
+<div class="mt-md-4 mt-3" [innerHtml]="greedyMetaData.applications"></div>
+<div class="mt-md-4 mt-3" [innerHtml]="greedyMetaData.advantage"></div>
+<div class="mt-md-4 mt-3" [innerHtml]="greedyMetaData.disadvantage"></div>

src/app/components/Algorithms/greedy/greedy-algorithm/greedy-algorithm.component.ts

@@ -1,12 +1,13 @@
 import { Component, OnInit } from '@angular/core';
+import { greedyMetaData } from 'src/app/core/algorithms/greedy-meta-data';
 
 @Component({
   selector: 'app-greedy-algorithm',
   templateUrl: './greedy-algorithm.component.html',
   styleUrls: ['./greedy-algorithm.component.css']
 })
 export class GreedyAlgorithmComponent implements OnInit {
-
+  greedyMetaData = greedyMetaData;
   constructor() { }
 
   ngOnInit(): void {

src/app/core/algorithms/greedy-meta-data.ts

@@ -0,0 +1,62 @@
+import { Helper } from "src/app/helper/helper"
+
+const greedyData = {
+   defination: `A greedy algorithm is an approach for solving a problem by selecting the best option available at the moment. 
+   It doesn't worry whether the current best result will bring the overall optimal result. <br>
+   The algorithm never reverses the earlier decision even if the choice is wrong. It works in a top-down approach.
+   <br>
+   This algorithm may not produce the best result for all the problems. It's because it always goes for the local best 
+   choice to produce the global best result.
+   `,
+   example: 'assets/ds-image/greedy.jpg',
+   properties:[
+    `<b>Greedy Choice Property:</b> If an optimal solution to the problem can be found by choosing the best choice at 
+    each step without reconsidering the previous steps once chosen, the problem can be solved using a greedy approach. 
+    This property is called greedy choice property.`,
+    `<b>Optimal Substructure:</b> If the optimal overall solution to the problem corresponds to the optimal solution to 
+    its subproblems, then the problem can be solved using a greedy approach. This property is called optimal substructure.`
+   ],
+   components:[
+    `<b>Candidate set:</b> A solution that is created from the set is known as a candidate set.`,
+    `<b>Selection function:</b> This function is used to choose the candidate or subset which can be added in the solution.`,
+    `<b>Feasibility function:</b> A function that is used to determine whether the candidate or subset can be used to contribute 
+      to the solution or not.`,
+    `<b>Objective function:</b> A function is used to assign the value to the solution or the partial solution.`,
+    `<b>Solution function:</b> This function is used to intimate whether the complete function has been reached or not.`,
+   ],
+   algorithm:[
+    `To begin with, the solution set (containing answers) is empty.`,
+    `At each step, an item is added to the solution set until a solution is reached.`,
+    `If the solution set is feasible, the current item is kept.`,
+    `Else, the item is rejected and never considered again.`
+   ],
+   applications:[
+    `Selection Sort`,
+    `Fractional knapsack Problem`,
+    `Minimum Spanning Tree(Prim's, Kruskal's,)`,
+    `Single-Source Shortest Path Problem`,
+    `Job Scheduling Problem`,
+    `Huffman Coding`,
+    `Ford-Fulkerson Algorithm`
+   ],
+   advantages: [
+    `The algorithm is easier to describe.`,
+    `This algorithm can perform better than other algorithms (but, not in all cases).`
+   ],
+   disadvantage: [
+    `As mentioned earlier, the greedy algorithm doesn't always produce the optimal solution. 
+    This is the major disadvantage of the algorithm`
+   ]
+}
+
+export const greedyMetaData = {
+    defination: Helper.setHeader(greedyData.defination),
+    example: Helper.setExampleImage('Greedy Approach', greedyData.example),
+    properties: Helper.setListwithTitleHtml('Properties of Greedy Algorithm', greedyData.properties),
+    components: Helper.setListwithTitleHtml('Components of Greedy Algorithm', greedyData.components),
+    algorithm: Helper.setListwithTitleHtml('Greedy Algorithm', greedyData.algorithm),
+    applications: Helper.setListwithTitleHtml('Applications of Greedy Algorithm', greedyData.applications),
+    advantage: Helper.setListwithTitleHtml('Advantages of Greedy Algorithm', greedyData.advantages),
+    disadvantage: Helper.setListwithTitleHtml('Disadvantages of Greedy Algorithm', greedyData.disadvantage),
+    
+}