Enhancing hybrid genetic algorithm performance in reducing steel usage for shipbuilding through sensitivity analysis

Figures & data

Figure 1. Workflow of optimization method.

Figure 2. SA procedure.

Figure 3. Plate grouping to GA process.

Figure 4. Hybrid GA procedure.

Figure 5. Hatch cover design (A type).

Table 1. Initial data.

Item	Unit	Initial design
L (length)	mm	10,675
W (width)	mm	9462
H (height)	mm	815
Load	N/mm^2	0.0343
Material	–	NS, AH32
Density	kg/m^3	7800
Stiffener (top plate)	mm^2	1362
Stiffener (bottom plate)	mm^2	2736

Table 2. Initial structure design.

Structure	Material type	Thickness (mm)
Plate 0-1	NS	9
Plate 2-3	AH32	11
Plate 4-5	NS	9
Plate 6-8	AH32	10
Plate 9	NS	8
Plate 10	AH32	14
Plate 11-12	AH32	10
Plate 13	AH32	16
Plate 14	NS	8
Plate 15	NS	10
Plate 16	NS	8
Plate 17	NS	10
Plate 18-19	NS	8

Table 3. Material properties.

Material type	Tensile strength (MPa)	Yield strength (MPa)	Density (kg/m^3)	Price ($/ton)^a
NS (normal strength)	400–502	235	7800	533
AH32 (higher strength)	440–590	315	7800	733
AH36 (higher strength)	490–620	355	7800	800

^aSteel Price (2019).

Figure 6. Stress changed distribution: (a) –2 mm, (b) +2 mm, (c) +3 mm and (d) +4 mm.

Figure 7. Plate simulation sequence.

Table 4. Summary of SA.

Group	Plate pairing
	−2 mm	+2 mm	+3 mm	+4 mm
1	3, 9	0, 18	0, 18	0, 18
2	4, 18	3, 9	3, 9	3, 9
3	6, 19	6, 13	6, 13	6, 13

Table 5. Results of comparison of SA with hybrid GA.

	Without optimization	Hybrid GA (I)	SA + Hybrid GA (II)	Difference (I and II)
Time (h)	–	54	18	−67%
Material cost ($)	7330	3971	3981	+0.25%

Figure 8. Plate thickness change.

Figure 9. Material type change.