Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models. Pyomo can be used to define symbolic problems, create concrete problem instances, and solve these instances with standard solvers. Pyomo supports a wide range of problem types, including:
Mixed-integer linear programming
Mixed-integer quadratic programming
Mixed-integer nonlinear programming
Mixed-integer stochastic programming
Generalized disjunctive programming
Differential algebraic equations
Mathematical programming with equilibrium constraints
Pyomo supports analysis and scripting within a full-featured programming language. Further, Pyomo has also proven an effective framework for developing high-level optimization and analysis tools. For example, the PySP package provides generic solvers for stochastic programming. PySP leverages the fact that Pyomo's modeling objects are embedded within a full-featured high-level programming language, which allows for transparent parallelization of subproblems using Python parallel communication libraries.
Pyomo development moved to this repository in June, 2016 from
Sandia National Laboratories. Developer discussions are hosted by google groups.
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