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PYthon Optimization Modeling Objects


Pyomo is a tool for formulating and analyzing mathematical models that represent real-world systems for complex optimization applications as applied in different areas of business, engineering, research, and administration. It's used to define symbolic problems, create concrete problem instances, and solve this instances with standard solvers. Pyomo provides a capability that is commonly associated with algebraic modeling languages (AML) and applications like AMPL, AIMMS, or GAMS, but has its modeling objects within the Python environment. Pyomo features a versatile set of modeling components, and supports concrete models (defined with data) as well as abstract models (defined without data).

For the processing of instantiated models Pyomo supports a wide range of independent solvers that could be written either in Python or other languages. Pyomo supports the general ASL (AMPL Solver Library) compatible interface, and has invidividual backends for solvers which some of them are available within Debian (GLPK, COIN-OR CPC, OPENOPT). Pyomo's solver manager could also employ the public NEOS Server to remotely optimize models if network access is available.

Pyomo was formerly released as the Coopr software library, and includes the PySP package (Pyomo Stochastic Programming) which provides generic solvers for stochastic programming.

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962 other people were interested in this package here. The newest known version of this software is 4.3.11388+git20160622.d3e3f0a-1 (Information last updated about 5 hours ago.)