pygmo is a scientific Python library for massively parallel optimization. It is
built around the idea of providing a unified interface to optimization
algorithms and problems, and to make their deployment in massively parallel
environments easy.

Efficient implementantions of bio-inspired and evolutionary algorithms are sided
to state-of-the-art optimization algorithms (Simplex Methods, SQP methods,
interior points methods, ...) and can be easily mixed (also with your
newly-invented algorithms) to build a super-algorithm exploiting algorithmic
cooperation via the asynchronous, generalized island model.

pygmo can be used to solve constrained, unconstrained, single objective,
multiple objective, continuous and integer optimization problems, stochastic and
deterministic problems, as well as to perform research on novel algorithms and
paradigms, and easily compare them to state-of-the-art implementations of
established ones.