Pyomos

Pyomos is an open-source Python library for formulating and solving mathematical optimization problems. It provides a high-level algebraic modeling language that allows users to define decision variables, constraints, and objective functions using Python expressions. The design emphasizes readability and modularity, enabling complex models to be built from reusable components.

Models in Pyomos are written by declaring variables with specified domains (continuous, integer, or binary), adding constraints as expressions over these variables, and specifying a scalar objective to minimize or maximize. The syntax is designed to resemble mathematical notation while benefiting from Python's programming capabilities, such as looping, data structures, and function calls.

Pyomos supports a range of problem types, including linear, mixed-integer, and nonlinear optimization. It provides an abstraction layer to connect to external solvers such as popular linear and integer programming engines, enabling users to solve problems without changing their modeling code. It can import and export standard formats for data exchange and can be integrated with Python data sources like lists, arrays, or CSV files.

Architecture-wise, Pyomos separates the modeling kernel from solver adapters, allowing the core API to stay solver-agnostic. The project emphasizes extensibility, with a plugin-like mechanism to add new solvers or problem features.

Licensing and usage: Pyomos is released under an open-source license and is used by researchers and practitioners to prototype models, reproduce experiments, and teach optimization concepts. Documentation and tutorials accompany the project to help new users start quickly.