feat: v0.2.3

• Add new parameter ensure_evaluations to DECC;
  • This parameter allows to stop the optimization process mid-cycle (previously, the processes only checked its condition after a cycle had been finished);
• Add new return information: number of FEs used to obtain the best solution;

fix: v0.2.2

• Add clipping to DECC-G;
• Ensure that all values are within the bounds provided for the function;
• Apply clip after multiplication by weights;

feat: v0.2.0

Minor refactor: use np.squeeze(...) instead of accessing index 0 of best_fitness in DECC and DECC-G optimizers;

v0.1.1: PyPI

Add the package to PyPI with correct classifiers and URLs: https://pypi.org/project/decc/

v0.1.0: Initial Release

First release, contains two optimizer:

• DECC, with DECC-O and DECC-H variants;
• DECC-G;