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