Selection method
|
α
|
β
|
ε
|
γ
|
α
′
|
β
′
|
---|
I
|
16.4500 (0.6088)
|
36.1980 (0.4769)
|
0.0074 (0.0094)
|
0.000034 (0.4659)
|
537.6500 (0.0112)
|
3.3400 (0.0232)
|
II
|
264.4100 (0.8873)
|
7.6514 (1.1634)
|
0.0038 (0.0255)
|
0.087352 (0.5497)
|
249.2100 (0.0052)
|
0.3900 (0.0942)
|
III
|
163.3700 (0.9756)
|
37.0826 (0.3589)
|
0.0049 (0.0846)
|
0.012519 (1.0388)
|
409.5300 (0.0316)
|
1.3200 (0.1752)
|
IV
|
42.3500 (0.8777)
|
39.2892 (0.3936)
|
0.0057 (0.0077)
|
0.000744 (0.2041)
|
468.5600 (0.0020)
|
2.9400 (0.0079)
|
- Results are shown for each method used to select the final solution. Method I selects the solution that minimises the Euclidean
- distance between the Pareto front population and the objective space origin; method II selects the best fit to a 5 deg saccade
- (objective 1); method III selects the best fit to a 10 deg saccade (objective 2); method IV selects the best fit to a 20 deg saccade
- (objective 3). Mean parameter values and coefficients of variation (shown in brackets) were calculated from 16 NSGA-II
- runs with a population size of 8000. Optimised parameter values for individual NSGA-II runs are listed in Additional file 1: Tables S8-S11