diff --git a/docs/user-guide/performance-history/perf-graphs.ipynb b/docs/user-guide/performance-history/perf-graphs.ipynb
index 0d4d1f4ca..f154dbba1 100644
--- a/docs/user-guide/performance-history/perf-graphs.ipynb
+++ b/docs/user-guide/performance-history/perf-graphs.ipynb
@@ -37,9 +37,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
    "source": [
     "import performance\n",
     "\n",
@@ -49,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -191,7 +200,7 @@
        "Study 4                                 0.000001  "
       ]
      },
-     "execution_count": 2,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -212,14 +221,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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atCnN69ioUSPLNUiuZcuWqlevns029z6v18zf31/S3Wvm6emZotx8HVOLJ6s/O2fPnrU8l/qll16y2d7cd79+/VS5cmXLsTNnzlieO9y2bVs5ONj+Xwvme+bvv//Wvn370j2P5B70nuzTp49MJpPi4uI0a9asFG2XL1+uK1eu6LXXXrM6Hhsba/l8NG7c2PI35l7t2rWzvE7vs/+4exjnbOvvnYODg+U51/b4ewcAAAAgeyAZDQAAAGRz06dPl8lkkiTduXNHPXr00J07dzLVhzlBYEuZMmUsr//8888U5fv27VOPHj0UGBgoJycnubm5yd3dXe7u7urbt68kpUiE2VKkSBGbx728vCyvb926ZVVWr149PfXUU5KkN998U9WqVdPEiRN19uzZdMdLS0JCgnbv3i1JKlu2bKrJNkkqX768JOn8+fO6ePFiqvXSO797z+1+5MmTR97e3jbLXF1dFRgYKMn6fTx//rwuXLggSSpXrpwlGXrvT548eSxt0kqQppY4vB/bt2+XdDeJlfw+vJf5PUjexl6xmZPC9zJ/eSO1cnd3d0lSdHR0qn1n5Wcn+XVKfv3u5eLioq+//toqKZ+8bZkyZVK9Z/Lly2epl5Gkupk97snixYurUaNGkqSpU6emGOOHH37QU089leKLJnv37lVcXJyktK9Lrly5VKhQIUlp33PZwcM450fx9w4AAABA9kAyGgAAAMjG5s2bpwULFmju3LkqW7aspLuro0eNGpWpfnLkyJFqWa5cuSyvr1y5YlU2efJk1axZU7NmzVKVKlU0e/Zsbdu2TTt37tTOnTv14YcfSpKSkpLSjSG1ldnJE8H39uPm5qbNmzerefPmMplM2r9/vwYNGqTixYurTJky+uijj9JMEKfm2rVrio+Pl3R3ZXRakpdfvnw51XrpnV9GrlF60nofpf9/L//991/LiuOwsDBL+cyZMy3J0Ht/cubMaal3732QXGrneT/MsXl6etpc0Wz2oO9BWlxdXR+o3DAMm8ez+rOT/H1P/hnPiORte/Xqleo906pVK0u9tO6ZtPp/kHvSvOr55MmT+v333y3H//77bwUHB6tv376WL/LYGjujn/207rns4GGc86P4ewcAAAAge3DK6gAAAAAA3J8LFy6oX79+6t69u15++WWVLFlSzzzzjBISEvT555+rdevWqlKlil3HTJ64OXLkiAYNGqSkpCQNGjRIX331VYr6J06csOv4thQuXFi//PKLzpw5o7lz52rp0qU6cuSITpw4oVGjRmn8+PH69ttv1aNHjwz3mVoCMb269ya2Hme2Yu3UqZMGDhyYbltb21I/DBl9H7Lbe/A4fHYyc4+n5Ysvvkh1i/PkChYseF/9P8g9+dJLL6lAgQK6cuWKpk6dqvr160u6u1La2dnZ5t+E+/nsZ4d7Li1P4jkDAAAAeHRIRgMAAADZkGEY6tGjh3x8fDR58mRJd5/JO2zYMI0cOVIJCQnq0aOH9u7dK2dn53T7i4mJSbXs+vXrltf58+e3vF68eLFlddubb755v6diN8WLF9eIESM0YsQInTx5UlOnTtU333yj2NhYvfbaa6pdu7ZKliyZob7y5MkjFxcXxcfH69q1a2nWTX59/Pz8HugcHlRa76P0/7HmyZPH8ozg5EnCHDlyqFatWg8vwEwqWLCgTpw4oejoaMXHx6e6Ovpxeg8y4nH47CR/39O7x9Nq6+fnZ/d7xl73pDnh/MUXX2jp0qWaPHmyvLy8NHPmTLVr10558+ZNc+yMfvbv555LnsxNLRkcGxub6X7vx6M6ZwAAAABPJrbpBgAAALKhr776Slu2bNHs2bOtnhH80UcfqXLlypKkw4cPa+TIkRnqL61nLB8/ftzyumbNmpbX4eHhltfm54je62E/F/Tq1avatWtXiuOlSpXS+PHj9fPPP0uS4uPjtWHDhgz36+TkZEmAHT9+PM0tZY8cOSJJKlq0aKrPD35UIiIidPPmTZtlt2/ftrzPyd/HIkWKqGjRopKkY8eOpdn/yZMn9f3339u85g9D3bp1Jd3d0jf5fXgv83sgSXXq1HnocT2ox+Gzk/w6HT16NNV6sbGxmjlzplauXGmzbXr3THBwsL7//nudP38+w7HZ857s06ePTCaT4uLiNGvWLC1dulQRERGWLbzvVb16dcvW68nvq3tdv35dly5dknR/91zyLfVTe664+bnZD9ujOmcAAAAATyaS0QAAAEA2c/ToUQ0fPlxDhgxJsT2us7OzZs2aZVlBOnr0aO3fvz/dPoODgxUXF2ezbMWKFZIkHx8fNW/e3HLc19fX8vr06dM22x46dCjdsR/EmjVr9Mwzzyg0NNRm+fPPP295bX5Gckb17t1b0t2VgsHBwTbr/P333zp8+LAkqW/fvpnq/2EwDEPr1q2zWbZ27VrLc7BffvllqzLzue7Zs0fnzp1Ltf8PP/xQb7zxhiIjI+0TcDp69OghJ6e7G3otXbrUZp2EhARLorRx48YqVqzYI4ntQTwOn53AwEA999xzkqSVK1cqMTHRZr2VK1eqZ8+e+uWXX2y2XbZsWapf1khISNArr7yiwYMHZ3prd3vdk8WLF1ejRo0kST/++KO+//57lSpVyrJl973c3d31yiuvSJI2bdqkqKgom/WS3499+vRJ93zuFRAQYHkdEhKSojwyMlL79u1Ls4/kOwUkf/+2bdum119/XXv27MlQLI/qnAEAAAA8mUhGAwAAANlIfHy8unTpolKlSqW66rlixYoaMWKEJFm26zYnIVMTGxtrs7/Nmzdr9erVkqSgoCCr1Xxt2rSxvB45cmSKrWaPHTum2bNnZ+zEHtCUKVNsHl+7dq0kydHRUS+88EKm+nz55ZfVsGFDSdI777yTYvViYmKi+vfvL0kqW7Zshp5r+7C5urrqk08+0Y0bN6yOR0dH66OPPpIkVatWTf/73/+sygcPHqyyZcsqKSlJr732mu7cuZOi74ULF2rp0qV69tln1bRp04d3EskUK1ZMH3zwgSRp0qRJNldHjxkzRufOnZOHh4cmTpz4SOJ6UI/LZ2fSpEny8PBQSEiIxo4dm6I8MjJSH330kVxdXfXOO+/YbPv3339r1KhRNvt/++23FRYWpnfeeUe5c+fOVGz2vCfNq6BPnDihrVu3proq2mzUqFEqUKCAoqOjU5y3dHdl+yeffCJJ6t69u2UFf2bkzZvXsovFsmXLUpQHBQVZViunpkCBAnJ3d7fEZPbLL7/ohx9+SHWXBFsexTkDAAAAeDLxzGgAAAAgG9i+fbtiY2O1ZMkSHTp0SF999ZW2bt2qwMBABQYGpqhbrVo1+fr6Kjw8XEeOHNHgwYPVunVrubu729xe9a233tKvv/6qEydOqEOHDsqRI4e2b9+uiRMnyjAMvfrqq3r77bet2lSpUkXDhw/XZ599psWLF+uff/5Rly5dlCdPHu3fv18TJ05U3rx5Ldu6bty4UdLdrZfd3Nwsv9++fVvS3a3CN27cqIIFC6ps2bK6fv269u3bZ7VCdPv27Tp9+rTKlSsnPz8/y8rA8ePH68iRI2rXrp0KFSqkGzduaMeOHZo+fbpMJpPGjRunMmXKWMb7448/bI6d/Po4Ojpq6dKlateunYKDg1W1alX1799fxYsX1+XLl/XDDz9o7969qlixolavXm2VqDfHfuXKFcuxffv2KSEhwRL72bNnLT/mWO69Rpnl6+urV155RdWrV9eAAQMUGBio8+fPa/Lkyfrrr79UrFgxLV261LLa2CxHjhxau3atWrZsqfXr16tq1arq27evihcvrn/++Ufr1q3TokWLVKFCBS1cuNCq7b59+3T9+nWFhYVZzt18Hub3Mrm0rr+tNiNGjNDNmzc1YcIE1a5dWwMHDlT16tV169YtLVmyREuWLFHu3Lm1ZMkSlStXzmqs1O4xSZb3IbmMvG/m8zU/OzcsLEwbN25Urly5VK1aNYWFhenYsWNWiXPzmNWqVVOuXLkei8+OJJUvX16//PKL2rdvrw8++ED79+9Xu3bt5O7urhMnTmjKlCkKDw/XzJkzVbp0aatrlbztiBEjtGvXLnXq1El58+bV+fPnNWvWLO3evVudO3e2fDkmMx7knrzXSy+9pAIFCujKlStyc3NT9+7d06zv5+en3377TS1bttT06dMVGhqq7t27K0+ePDp27JgmTJigsLAw/e9//9P3339v1db8tzojn+tRo0apVatWmjVrlhITE9W8eXM5Oztr0aJFunPnjtq0aaPZs2dbfaYaNWpked60o6Oj2rdvrzlz5mjs2LFyc3PTlStX9P3338vf319169a13I+27unkn7UHOWfz3zFb97z5nFP73KQ2JwEAAAD4DzEAAAAAPPb8/f0NSSl+RowYkeG6kgx/f3+bdUeMGGHExMQYI0aMMMqVK2d4eHgYXl5exrPPPmssWLAgzdhWrlxpPP/880bOnDkNJycnI1++fEbTpk2NRYsWGTNmzEgRQ0hIiGEYRqoxdu/e3TAMwwgODk61zowZMyzj796923j//feNOnXqGPny5TOcnJwMNzc3o0SJEkaPHj2MPXv2WMUbEhKS4etjGIaRlJRkzJ8/32jWrJmRP39+w9nZ2cidO7fRsGFD4/vvvzfi4+NTtMlI7CNGjEi1jvkaZZS5L3P8q1atMho3bmzkyZPHcHFxMUqUKGG8//77RmRkZJr9xMfHGz/88IPRsGFDI0+ePIajo6ORK1cu49lnnzW+/vprIy4uLkWb+vXrp/teJpfW9U+tjWEYxs6dO40uXboYRYsWNVxcXAwvLy+jSpUqxkcffWRERETYbJPWOMnvIbOMvG+pnW/9+vUNwzBs3vPmn+DgYKvxsvqzYxYREWF8/PHHRpUqVQxvb2/D2dnZKFKkiNGtWzfj8OHDNq9tam2dnJwMX19fo1WrVsbKlSvTbJsR93NP2jJ06FBDktGlS5cMjx0dHW2MHTvWqFWrlpEzZ07D2dnZKFiwoNG2bVvj119/tdkmrb+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       "text/plain": [
-       "<Figure size 1500x800 with 3 Axes>"
+       "<Figure size 2000x800 with 4 Axes>"
       ]
      },
      "metadata": {},
diff --git a/docs/user-guide/performance-history/perf_data.json b/docs/user-guide/performance-history/perf_data.json
index d6f522ef4..a66ca4229 100644
--- a/docs/user-guide/performance-history/perf_data.json
+++ b/docs/user-guide/performance-history/perf_data.json
@@ -41,6 +41,13 @@
                     "antares": 363,
                     "problem_generation": 453,
                     "benders": 1111
+                },
+                {
+                    "version": 1.4,
+                    "batch_size": 96,
+                    "antares": 313,
+                    "problem_generation": 347,
+                    "benders": 1061
                 }
             ]
         },
@@ -85,6 +92,13 @@
                     "antares": 434,
                     "problem_generation": 444,
                     "benders": 980
+                },
+                {
+                    "version": 1.4,
+                    "batch_size": 96,
+                    "antares": 360,
+                    "problem_generation": 345,
+                    "benders": 957
                 }
             ]
         },
@@ -129,6 +143,13 @@
                     "antares": 383,
                     "problem_generation": 435,
                     "benders": 1014
+                },
+                {
+                    "version": 1.4,
+                    "batch_size": 96,
+                    "antares": 384,
+                    "problem_generation": 350,
+                    "benders": 1107
                 }
             ]
         },
@@ -173,6 +194,13 @@
                     "antares": 517,
                     "problem_generation": 569,
                     "benders": 521
+                },
+                {
+                    "version": 1.4,
+                    "batch_size": 96,
+                    "antares": 283,
+                    "problem_generation": 393,
+                    "benders": 544
                 }
             ]
         }