Crossover versus Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems

Table 12

Convergence behaviour of the nine techniques applied to the BPP.

BPP	GA1		GA2		EA1
Instance	Avg.	St.d.	Avg.	St.d.	Avg.	St.d.
N2C1W1_A	134.4	85.0	143.8	76.8	128.7	88.8
N2C1W1_B	64.8	24.6	112.8	81.4	86.9	34.7
N3C2W2_A	332.1	144.1	384.9	153.7	301.2	185.7
N3C2W2_B	356.4	116.7	345.1	128.0	314.8	111.0
N3C3W1_A	298.7	102.4	310.8	117.0	332.1	98.6
N3C3W1_B	366.0	176.8	410.2	218.4	385.8	158.4
N4C1W1_A	1542.3	312.7	1569.7	583.9	1328.6	586.9
N4C1W1_B	1663.4	497.8	1682.4	597.7	1538.7	486.8
N4C1W1_C	1364.8	599.4	1473.1	757.2	1499.4	584.7
N4C2W1_A	1340.0	573.0	1495.5	674.6	1616.4	473.5
Instance	GA3		GA4		EA2
N2C1W1_A	151.7	80.8	132.2	81.2	112.7	90.7
N2C1W1_B	87.4	43.1	95.6	42.2	100.3	56.1
N3C2W2_A	232.7	101.8	299.4	81.4	285.7	91.3
N3C2W2_B	371.5	120.7	301.4	114.7	350.0	103.3
N3C3W1_A	312.8	136.9	358.7	136.2	299.5	77.0
N3C3W1_B	351.7	146.2	400.7	187.4	411.4	101.3
N4C1W1_A	1501.1	304.7	1499.0	608.9	1482.4	499.9
N4C1W1_B	1452.8	531.5	1577.3	519.0	1490.2	503.1
N4C1W1_C	1612.7	671.4	1579.0	676.3	1535.8	555.3
N4C2W1_A	1315.8	500.4	1399.4	741.2	1584.4	463.9
Instance	GA5		GA6		EA3
N2C1W1_A	114.0	73.4	100.4	57.1	142.7	90.4
N2C1W1_B	81.4	21.1	71.8	27.4	95.7	43.8
N3C2W2_A	300.2	112.4	327.1	99.7	350.2	198.7
N3C2W2_B	376.4	132.4	355.4	140.5	299.4	134.5
N3C3W1_A	280.7	139.5	273.0	113.6	350.7	102.7
N3C3W1_B	481.8	241.5	451.9	223.4	371.4	188.0
N4C1W1_A	1427.0	299.9	1500.2	531.5	1286.7	499.7
N4C1W1_B	1701.8	513.8	1759.0	642.3	1612.0	500.1
N4C1W1_C	1310.8	524.3	1210.4	571.8	1571.0	611.4
N4C2W1_A	1274.0	497.9	1379.6	573.4	1527.1	511.7