Opti is a Python package for specifying problems in a number of closely related fields, including experimental design, multiobjective optimization, decision making and Bayesian optimization.
Docs: https://basf.github.io/mopti/
Code: https://github.com/basf/mopti
Opti ...
- supports mixed continuous, discrete and categorical parameter spaces for system inputs and outputs,
- separates objectives (minimize, maximize, close-to-target) from the outputs on which they operate,
- supports different specific and generic constraints as well as black-box output constraints,
- provides sampling methods for constrained mixed variable spaces,
- json-serializes problems for use in RESTful APIs and json/bson DBs, and
- provides a range of benchmark problems for (multi-objective) optimization and Bayesian optimization.
We are developing a successor of opti called BoFire and recommend using that. To help you with the transition to BoFire there is https://github.com/experimental-design/bofire-converters.
