OptimTemplates v1.3.1
Updates:
- NSGA2 now supports using Eigen's array types (
Eigen::Array<double,...>
) as fitness value with vectorized implementation of selection operation. - NSGA2 now supports working with runtime objective numbers.
Changes:
- New classes: MOGAAbstract, MOGABase, NSGABase, NSGA2Base (All of them are used to reduce code duplication while supporting runtime objective numbers and boosting with eigen arrays).