documentation//notebooks//demo//paper

Paref - problem tailored MOO for expensive black-box functions

A multi-objective optimization (MOO) problem comes with an idea of what properties the identified (Pareto) points must satisfy. The fact that these properties are satisfied is what makes a MOO successful in the first place. Why not construct MOO algorithms that search for exactly these properties and, by their very nature, use only a minimum number of evaluations? With the language of PAreto REFlections this is now possible. This package contains...

• a series of ready-to-use MOO algorithms corresponding to frequently targeted properties
• a framework for you to implement your problem tailored MOO algorithm
• generic and intuitive interfaces for MOO algorithms, black-box functions and more, so solving a MOO problem with user-defined properties with Paref requires only minimal effort

See the official documentation for more information.

The official release is available at PyPi:

pip install paref