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dsnalzamidsnalzami
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add description for graphviz
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‎3d_tic_tac_toe/3d_tic_tac_toe.ipynb

+27-23
Original file line numberDiff line numberDiff line change
@@ -145,7 +145,8 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Using license file c:\\gurobi\\gurobi.lic\n"
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"Set parameter Username\n",
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"Academic license - for non-commercial use only - expires 2024-04-29\n"
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]
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}
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],
@@ -221,50 +222,53 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Gurobi Optimizer version 9.1.0 build v9.1.0rc0 (win64)\n",
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"Thread count: 4 physical cores, 8 logical processors, using up to 8 threads\n",
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"Gurobi Optimizer version 10.0.2 build v10.0.2rc0 (win64)\n",
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"\n",
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"CPU model: AMD Ryzen 7 5800H with Radeon Graphics, instruction set [SSE2|AVX|AVX2]\n",
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"Thread count: 8 physical cores, 16 logical processors, using up to 16 threads\n",
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"\n",
226230
"Optimize a model with 1 rows, 76 columns and 27 nonzeros\n",
227-
"Model fingerprint: 0xcbf7569f\n",
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"Model fingerprint: 0x9039be95\n",
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"Model has 98 general constraints\n",
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"Variable types: 0 continuous, 76 integer (76 binary)\n",
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"Coefficient statistics:\n",
231235
" Matrix range [1e+00, 1e+00]\n",
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" Objective range [1e+00, 1e+00]\n",
233237
" Bounds range [1e+00, 1e+00]\n",
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" RHS range [1e+01, 1e+01]\n",
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" GenCon rhs range [1e+00, 2e+00]\n",
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" GenCon coe range [1e+00, 1e+00]\n",
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"Presolve added 98 rows and 0 columns\n",
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"Presolve time: 0.00s\n",
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"Presolved: 99 rows, 76 columns, 419 nonzeros\n",
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"Variable types: 0 continuous, 76 integer (76 binary)\n",
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"Found heuristic solution: objective 7.0000000\n",
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"\n",
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"Root relaxation: objective 0.000000e+00, 46 iterations, 0.00 seconds\n",
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"Root relaxation: objective 0.000000e+00, 42 iterations, 0.00 seconds (0.00 work units)\n",
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"\n",
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" Nodes | Current Node | Objective Bounds | Work\n",
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" Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time\n",
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"\n",
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" 0 0 0.00000 0 8 7.00000 0.00000 100% - 0s\n",
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"H 0 0 5.0000000 0.00000 100% - 0s\n",
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" 0 0 0.00000 0 18 5.00000 0.00000 100% - 0s\n",
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"H 0 0 6.0000000 0.00000 100% - 0s\n",
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"H 0 0 4.0000000 0.00000 100% - 0s\n",
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" 0 0 0.00000 0 19 4.00000 0.00000 100% - 0s\n",
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" 0 0 0.00000 0 8 4.00000 0.00000 100% - 0s\n",
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" 0 0 0.00000 0 18 4.00000 0.00000 100% - 0s\n",
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" 0 0 0.00000 0 21 4.00000 0.00000 100% - 0s\n",
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" 0 0 0.50000 0 8 4.00000 0.50000 87.5% - 0s\n",
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" 0 0 0.66667 0 18 4.00000 0.66667 83.3% - 0s\n",
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" 0 0 1.00000 0 8 4.00000 1.00000 75.0% - 0s\n",
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" 0 0 1.00000 0 8 4.00000 1.00000 75.0% - 0s\n",
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" 0 2 1.00000 0 8 4.00000 1.00000 75.0% - 0s\n",
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" 0 0 0.33333 0 8 4.00000 0.33333 91.7% - 0s\n",
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" 0 0 0.50000 0 19 4.00000 0.50000 87.5% - 0s\n",
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" 0 0 0.66667 0 10 4.00000 0.66667 83.3% - 0s\n",
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" 0 0 0.66667 0 10 4.00000 0.66667 83.3% - 0s\n",
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" 0 2 0.66667 0 8 4.00000 0.66667 83.3% - 0s\n",
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"\n",
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"Cutting planes:\n",
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" MIR: 4\n",
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" Inf proof: 9\n",
262-
" Zero half: 14\n",
264+
" MIR: 7\n",
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" Inf proof: 13\n",
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" Zero half: 17\n",
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"\n",
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"Explored 2139 nodes (14255 simplex iterations) in 0.26 seconds\n",
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"Thread count was 8 (of 8 available processors)\n",
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"Explored 3780 nodes (23250 simplex iterations) in 0.17 seconds (0.11 work units)\n",
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"Thread count was 16 (of 16 available processors)\n",
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"\n",
267-
"Solution count 3: 4 5 7 \n",
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"Solution count 3: 4 6 7 \n",
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"\n",
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"Optimal solution found (tolerance 1.00e-04)\n",
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"Best objective 4.000000000000e+00, best bound 4.000000000000e+00, gap 0.0000%\n"
@@ -292,9 +296,9 @@
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"outputs": [
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{
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"data": {
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"image/png": "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\n",
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"image/png": "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",
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"text/plain": [
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"<Figure size 720x360 with 3 Axes>"
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"<Figure size 1000x500 with 3 Axes>"
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]
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},
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"metadata": {},
@@ -355,7 +359,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.17"
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"version": "3.10.12"
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}
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},
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"nbformat": 4,

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