A Design Optimization Method with Sparse Scattered Data and Evolutionary Computation

Table 4

The design solutions in nondominated Pareto front of 4 runs.

Run #	Run 1				Run 2
1	12	0	13	3.3	12	0	13	3.2
2	12	0	13	3.4	12	0	13	3.3
3	12	0.4	7	3.5	12	0	13	3.4
4	12.8	0.4	7	3.5	12	0	7	3.5
5	12.8	0.8	7	3.5	12	0.4	7	3.5
6	13.6	0.8	7	3.5	12.8	0.4	7	3.5
7	13	0.5	7.1	3.5	12.8	0.5	7	3.5
8	12.8	0.9	7.1	3.5	13	0.6	7	3.5
9	13	0.9	7.1	3.5	12.9	0.8	7	3.5
10	12.8	0.4	7.3	3.5	13	0.6	7.1	3.5
11	12.8	0.4	7.7	3.5	12	0	13	3.5
12	12	0	13	3.5	13.2	0.8	7	3.6
13	12.8	0.4	7	3.7	12.9	0.7	7	3.8
14	12.8	0.8	7	3.9	12.9	0.8	7	3.8
15	12	0.7	13	4.6	12.9	0.8	7.1	3.8
16	12	0.7	13	4.7	12	0.7	13.1	4.7
17	12	0.7	13	4.8	12	0.5	13.1	4.8
18	12	0.7	13.1	4.9	12	0.6	13.1	4.8
19	12	0.9	13.1	4.9	12	0.6	13.1	4.9
20	12	0.9	13.7	4.9	12	0.8	13.1	4.9
Run #	Run 3				Run 4
1	12	0	13	3.2	12	0	13	3.3
2	12	0	13	3.3	12	0	13	3.4
3	12	0	13	3.4	12	0	7	3.5
4	12	0	7	3.5	12.8	0.4	7	3.5
5	12.8	0.4	7	3.5	12.8	0.5	7	3.5
6	13.2	0.5	7	3.5	12.8	0.9	7	3.5
7	12.8	0.8	7	3.5	12.8	1.1	7	3.5
8	13.2	1.2	7	3.5	12	0	13	3.5
9	12.8	0.6	7.2	3.5	12.8	0.6	7	3.6
10	13	0.6	7.4	3.5	12.8	0.7	7	3.6
11	12	0	13	3.5	13	0.7	7	3.6
12	12.8	0.9	7	3.6	12.9	1	7	3.7
13	12.8	0.4	7	3.8	12.8	0.5	7	3.8
14	12.8	0.6	7	4.1	12.8	0.5	7	4
15	12	0.4	13	4.8	12	0.4	13	4.5
16	12	0.7	13	4.8	12	0.4	13	4.6
17	12	0.7	13.1	4.8	12	1.4	13	4.7
18	12	0.9	13.1	4.8	12	0.2	13	4.8
19	12	0.4	13	4.9	12	0.4	13	4.8
20	12	1.2	13.1	4.9	12	0.4	13	4.9