Plot descriptions

Author: adhishagc

Genetic_Algorithm_Assignment.ipynb

@@ -955,35 +955,55 @@
         }
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "nGw3JHBKp1_J",
+        "colab_type": "text"
+      },
+      "source": [
+        "### **Plotting the Final Result**\n",
+        "\n",
+        "This plot shows 3 import facts about the final solution. \n",
+        "\n",
+        "\n",
+        "1.   The Horizontal Line shows the 4,500MB benchmark line\n",
+        "2.   The Zig Zag plot shows the Fitness of the Final Population\n",
+        "3. The Red Cross (+) shows the position of the Optimum solution Generated\n",
+        "\n",
+        "\n",
+        "\n"
+      ]
+    },
     {
       "cell_type": "code",
       "metadata": {
         "id": "4DYhr1UnHHC0",
         "colab_type": "code",
-        "outputId": "92020dc7-0ee6-41e1-8eb3-dc4d959413e6",
+        "outputId": "47f29ba3-ce9d-403a-ef0c-bae7d765e9ad",
         "colab": {
           "base_uri": "https://localhost:8080/",
           "height": 286
         }
       },
       "source": [
         "plt.plot([x for x in range(popSize)],[finalSize[x] for x in range(len(finalSize))])\n",
-        "plt.plot([finalDuration.index(max(finalDuration))],[finalSize[finalDuration.index(max(finalDuration))]],'r+')\n",
+        "plt.plot([Best_Solution_id],[Best_Solution_Size],'r+')\n",
         "plt.plot([x for x in range(popSize)],[4500 for x in range(len(finalSize))])"
       ],
-      "execution_count": 21,
+      "execution_count": 32,
       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "[<matplotlib.lines.Line2D at 0x7f3903cc7a20>]"
+              "[<matplotlib.lines.Line2D at 0x7f390110c358>]"
             ]
           },
           "metadata": {
             "tags": []
           },
-          "execution_count": 21
+          "execution_count": 32
         },
         {
           "output_type": "display_data",