Hybrid Genetic Algorithm with Multiparents Crossover for Job Shop Scheduling Problems
Table 2
Output for different crossover rates and mutation rates.
Mut_01
Mut_02
Mut_03
Mut_04
Mut_05
Mut_06
Mut_07
Mut_08
Mut_09
Mut_10
Average
Relative error (%)
Crs_10
971.96
978.20
972.64
968.06
969.28
972.34
971.58
965.46
963.24
968.12
970.09
4.31
Crs_9
967.38
975.94
965.82
968.24
970.30
965.36
963.44
961.14
961.00
960.32
965.89
3.86
Crs_8
971.54
968.00
967.24
965.92
966.10
964.28
964.58
958.92
958.84
959.12
964.45
3.70
Crs_7
973.94
968.32
969.26
963.72
963.48
961.58
958.46
957.84
959.02
958.94
963.46
3.60
Crs_6
972.96
968.32
969.30
965.26
964.02
965.10
964.08
960.16
959.90
959.58
964.87
3.75
Crs_5
971.88
975.96
975.60
969.12
962.58
967.36
960.92
961.60
961.04
957.10
966.32
3.90
Crs_10 represents crossover rate at 1.0, Crs_9 represents crossover rate at 0.9, and so on. Mut_01 represents mutation rate at 0.1, Mut_02 represents mutation rate at 0.2, and so on.
