## 5 Computational Results
### Algorithm Results
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline
**Class A** & **CTLEX** & \multicolumn{3}{c}{**LALINGM (\(J=10\))**} & \multicolumn{3}{c}{**LALINGM (\(J=20\))**} & \multicolumn{3}{c}{**LALINGM (\(J=80\))**} \\ \hline
**Instance** & **Objective** & **Time** & **Objective** & **Time** & **Inetions** & **Objective** & **Time** & **Inetions** & **Objective** & **Time** & **Inetions** & **Objective** & **Time** & **Inetions** \\ \hline
1 & 600.72 & 1800.0 & 15535.14 & 10.6 & 5 & 5789.71 & 56.6 & 37 & 5704.71 & 56.8 & 52 & 5799.71 & 406.5 & 69 \\
2 & 600.92 & 1800.0 & 12173.29 & 101.8 & 3 & 664.55 & 229.8 & 27 & 589.21 & 25.5 & 80 & 5483.83 & 506.8 & 88 \\
3 & 4597.86 & 1800.0 & 9067.1 & 241.8 & 8 & 9046.23 & 204.3 & 13 & **9002.43** & 208.9 & 29 & 4258.88 & 800.00 & 120 \\
4 & 1904.40 & 1800.0 & 8799.06 & 235.8 & 4 & 8477.86 & 922.5 & 38 & 8813.84 & 112.88 & 57 & **5808.00** & 1558.88 & 94 \\
5 & 6332.66 & 1800.0 & 14568.55 & 119.9 & 4 & **8080.00** & 407.5 & 36 & **7733.80** & 65.8 & 45 & 5757.81 & 489.5 & 57 \\
6 & 7272.14 & 1800.0 & **7224.21** & 12.4 & 4 & 7792.24 & 322.5 & 19 & **7922.41** & 622.2 & 46 & **7292.38** & 1172.7 & 76 \\
7 & 5071.43 & 1800.0 & 14831.85 & 102.6 & 7 & 5303.71 & 296.6 & 30 & **4587.57** & 208.9 & 39 & **6424.34** & 543.6 & 65 \\
8 & 7044.71 & 1800.0 & 17237.32 & 125.8 & 7 & 8187.88 & 293.4 & 34 & 7118.4 & 407.5 & 39 & **6427.86** & 66 & 66 \\
9 & 7264.14 & 1800.0 & 9596.26 & 116.5 & 5 & 5302.82 & 732.2 & 30 & 5034.57 & 619.8 & 28 & 7733.44 & 114.2 & 112 \\
10 & 9792.00 & 1800.0 & 4620.72 & 29.9 & 11 & **5888.48** & 460.5 & 39 & 4002.52 & 45.5 & 45 & 5884.85 & 935.6 & 86 \\
11 & 5000.00 & 1800.0 & 4607.17 & 10.5 & 5 & **4780.00** & 55 & 44 & **4685.71** & 501.3 & 35 & **4354.2** & 54 & 78 \\
12 & 4625.00 & 1800.0 & 46328.58 & 14.4 & 9 & **4978.78** & 251.3 & 32 & **4492.93** & 304.4 & 41 & 4485.7 & 156 & 74 \\
13 & 5150.00 & 1800.0 & 5908.75 & 166.8 & 7 & **4778.58** & 251.8 & 18 & **3935.71** & 304.4 & 44 & **3967.77** & 395.6 & 65 \\
14 & 6927.00 & 1800.0 & 7777.00 & 299.8 & 12 & 704.02 & 318.5 & 13 & **6359.00** & 209.0 & 27 & **6370.00** & 40 & 54 \\
15 & 5136.14 & 1800.0 & 5540.3 & 17 & 6 & **5538.28** & 311.5 & 2 & **4964.44** & 34 & 53 & **5358.88**
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c} \hline
**Class A** & **C/LEX** & \multicolumn{3}{c}{**LARCH (\(l=1\))**} & \multicolumn{3}{c}{**LARCH (\(l=10\))**} & \multicolumn{3}{c}{**LARCH (\(l=20\))**} & \multicolumn{3}{c}{**LARCH (\(l=50\))**} \\ \hline
**Instance** & **Objective** & **Time** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** \\ \hline
47 & 7434.4 & 1800.0 & 8172.43 & 31.5 \(\bullet\) & 4 & 6880.43 & 733.55 & 26 & **84210.40** & 51.4 \(\bullet\) & 30 & **6900.42** & 865.5 \(\bullet\) & 57 \\
48 & 8093.7 & 1800.0 & 88187.27 & 139.5 \(\bullet\) & 4 & 9898.99 & 266.6 \(\bullet\) & 48 & **7403.34** & 400.3 \(\bullet\) & 34 & **6978.15** & 1423.5 \(\bullet\) & 83 \\
49 & 6721.14 & 1800.0 & **46420.29** & 140.8 \(\bullet\) & 7 & **8402.02** & 325.5 \(\bullet\) & 21 & **8823.71** & 386.5 \(\bullet\) & 33 & **8725.71** & 860.3 \(\bullet\) & 62 \\
50 & 6238.4 & 1800.0 & 88503.66 & 247.5 \(\bullet\) & 8 & 6304.43 & 475.5 \(\bullet\) & 24 & **8400.05** & 550.0 \(\bullet\) & 51 & **4900.85** & 1208.5 \(\bullet\) & 103 \\ \hline \(w_{5}\) & 6238.99 & 1800.00 & 8864.68 & 1579.66 & 5.2 & 5888.03 & 382.22 & 285.50 & 5698.36 & 5600.68 & 43.62 & 5820.74 \(\bullet\) & 875.92 & 83.28 \\ Gap C/C/LEX & \multirow{2}{*}{5} & \multirow{2}{*}{+409.9\%} & \multirow{2}{*}{+912.2\%} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-78.5\%} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{-} \\ (in \(\%\)) & & & & & & & & & & & & &  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline
**Class B** & **C/LEX** & \multicolumn{4}{c}{**LARCM (\(d=1\))**} & \multicolumn{4}{c}{**LARCM (\(d=20\))**} & \multicolumn{4}{c}{**LARCM (\(d=50\))**} \\ \hline
**Isstance** & **Objective** & **Time** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** \\ \hline
25 & 2978.30 & 89.5 & 3168.00 & 34  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline
**Class C** & \multicolumn{2}{c}{**CPLEX**} & \multicolumn{2}{c}{**LAKCM (\(l=1\))**} & \multicolumn{2}{c}{**LAKCM (\(l=10\))**} & \multicolumn{2}{c}{**LAKCM (\(l=20\))**} & \multicolumn{2}{c}{**LAHCM (\(l=50\))**} \\ \hline
**Instance** & **Objective** & **Time** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** \\ \hline  
13 & 141.8 & 44 & **22345.38** & 175 & 48 & **224463.37** & 127  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c} \hline \hline
**Class C** & \multicolumn{2}{c}{**CPLEX**} & \multicolumn{2}{c}{**LALKCM (\(d=10\))**} & \multicolumn{2}{c}{**LALKCM (\(d=20\))**} & \multicolumn{2}{c}{**LALKCM (\(d=50\))**} \\ \hline
**Instance** & **Objective** & **Time** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** & **Objective** & **Time** & **Iterations** \\ \hline
41 & 22704.38 & 1800.9 & 35307.63 & 105.8 & 5 & 24364.38 & 116.6 & 25 & 24071.00 & 138.9 & 39 & 22871.00 & 170.8 & 88 \\
42 & 38450.13 & 1800.8 & 53822.38 & 103.8 & 4 & 38070.12 & 138.8 & 31 & 38650.13 & 170.8 & 45 & 38605.13 & 308.3 & 132 \\
43 & 60703.63 & 1800.8 & 53004.37 & 106.8 & 4 & 52504.84 & 140.8 & 32 & 50056.38 & 128.9 & 34 & 47906.34 & 204.8 & 84 \\
44 & 33453.00 & 1800.8 & 31965.0 & 106.8 & 4 & 33550.03 & 125.8 & 18 & 39503.0 & 124.8 & 31 & 33550.0 & 199.8 & 86 \\
45 & 22222.75 & 1800.8 & 23462.13 & 105.8 & 4 & 22774.75 & 118.8 & 17 & 222927.75 & 161.8 & 46 & 22222.75 & 172.8 & 71 \\
46 & 27073.75 & 1800.8 & 48213.75 & 105.8 & 6 & 46131.75 & 122.2 & 22 & 470645.75 & 122.8 & 23 & **7673.75** & 180.8 & 73 \\
47 & 27461.38 & 1800.8 & 29969.13 & 99 & 4 & 29673.71 & 19.9 & 20 & 30082.5 & 145.8 & 41 & 203.2 & 271.8 & 71 \\
48 & 27636.35 & 1800.8 & 49408.8 & 101.8 & 5 & 49409.88 & 109.8 & 13 & 48163.63 & 128.3 & 33 & **27643.0** & 173.8 & 75 \\
49 & 52920.00 & 1800.8 & 65203.49 & 105.8 & 9 & 56111.87 & 138.8 & 34 & 59506.87 & 126.5 & 67 & 59509.18 & 187.5 & 75 \\
50 & 19509.25 & 1800.8 & 21010.25 & 108.8 & 6 & 20570.75 & 129.9 & 42 & 19759.25 & 162.5 & 55 & **19509.25** & 185.8 & 68 \\ \hline avg.