A C++ / Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model. State of the art optimization algorithms are included. A common interface is provided to other optimization frameworks/algorithms such as NLOPT, SciPy, SNOPT, IPOPT, GSL
C++ Python C CMake
Latest commit 881e2d2 Jan 20, 2017 @darioizzo darioizzo committed on GitHub BugFix - now velocity is set not the chromosome.



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Parallel Global Multiobjective Optimizer (and its Python alter ego PyGMO) offers a user-friendly access to a wide array of global and local optimization algorithms and problems. The main purpose of the software is to provide a parallelization engine common to all algorithms through the 'generalized island model'. Initially developed within the European Space Agency, the code was intended to help the automated design of interplanetary trajectories and spacecraft transfers in general. The user can implement his own problem and algorithm both in C++ and in Python.

Check the doxygen for PaGMO at http://esa.github.io/pagmo

Check the sphinx for PyGMO (the PaGMO Python bindings) at http://esa.github.io/pygmo