Pymoo

- New Algorithm: Nelder Mead with box constraint handling in the design space
- New Performance indicator: Karush Kuhn Tucker Proximity Measure (KKTPM)
- Added Tutorial: Equality constraint handling through customized repair
- Added Tutorial: Subset selection through GAs
- Added Tutorial: How to use custom variables
- Bugfix: No pf given for problem, no feasible solutions found

- Merging pymop into pymoo - all test problems are included
- Improved Getting Started Guide
- Added Visualization
- Added Decision Making
- Added GD+ and IGD+
- New Termination Criteria “x_tol” and “f_tol”
- Added Mixed Variable Operators and Tutorial
- Refactored Float to Integer Operators
- Fixed NSGA-III Normalization Variable Swap
- Fixed casting issue with latest NumPy version for integer operators
- Removed the dependency of Cython for installation (.c files are delivered now)

- New documentation and webpage (https://pymoo.org)
- Improved version of Differential Evolution (jitter, dither)
- New crossovers (UX, HUX, ...)
- R-NSGA-II Implementation added

First release of this optimization framework that is stored online.