pagmo 2.13.0
In this release of pagmo, the batch fitness evaluation framework has been completed on the Python side. This means that now it is possible to exploit fine-grained parallelisation (e.g., parallel initialisation of populations/islands/archipelagos, parallelisation of the inner loops of some algorithms, etc.) also for user-defined problems implemented in Python. Two pythonic batch fitness evaluators are available, one based on multiprocessing and the other using ipyparallel instead (which makes it possible to do parallel objective function evaluations on a cluster).
This release also contains a couple of important bugfixes, one of them fixing a crash due to mishandling of NaN values in the hypervolume utilities.
NOTE: as anticipated, in this release of pygmo Python 2.7 support has been dropped. pygmo now requires at least Python 3.4.
The full changelog, as usual, is available here: