Assembly Line Balancing Based on Beam Ant Colony Optimisation
Table 2
Characteristics of tricky instances.
Instances
C
Sum
Mean
Var
TV
OS
Barthol2
85
4234
28.608
356.716
1
83
83
0.012
0.977
0.337
0.258
Lutz2
12
485
5.449
8.205
1
10
10
0.083
0.833
0.454
0.776
Lutz2
14
485
5.449
8.205
1
10
10
0.071
0.714
0.389
0.776
Lutz3
110
1644
18.472
184.525
1
74
74
0.009
0.673
0.168
0.776
Lutz3
118
1644
18.472
184.525
1
74
74
0.009
0.627
0.157
0.776
Sawyer
47
324
10.800
36.855
1
25
25
0.021
0.532
0.230
0.448
Tonge
251
3510
50.143
1505.400
1
156
156
0.004
0.622
0.200
0.200
Warnecke
60
1548
26.690
206.077
7
53
7.571
0.117
0.883
0.445
0.591
Wee-mag
47
1499
19.987
46.419
2
27
13.5
0.043
0.575
0.425
0.227
Scholl
1394
69655
234.529
38911.047
5
1386
277.2
0.004
0.994
0.168
0.582
Scholl
2247
69655
234.529
38911.047
5
1386
277.2
0.002
0.617
0.104
0.582
Note. For instances of Scholl, only the statistical information of tricky instances with the smallest and largest cycle time is reported in order to show the tendency character of the problem; “Sum” in the second column is the sum of processing times; and “” and “” denote the minimum and maximum task time, respectively.
