Coopr 3.1 Release

We are pleased to announce the release of Coopr 3.1 (3.1.5325). Coopr is a collection of Python software packages that supports a diverse set of optimization capabilities for formulating and analyzing optimization models.

The following are highlights of Coopr 3.1:

  • Solvers
    • Interfaces for OpenOpt solvers
    • Many solver interface improvements
    • A solver checker to validate solver interfaces
    • Improved support for SOS constraints (cplex, gurobi)
    • PH supports nonlinear models
    • PH-specific solver servers
  • Modeling
    • Comprehensive rework of blocks and connectors for modular modeling
    • New VarList component
    • Added comprehensive support for set expressions
  • Usability enhancements
    • New 'coopr' command has subcommands that consolidate Coopr scripting
    • Added support to connect to databases with ODBC
    • Made JSON the default results format
  • Other
    • Efficiency improvements in model generation, memory, runtime, etc.
    • Preliminary support for black-box applications
    • Deprecated modeling syntax in Coopr 3.0 is no longer legal

See  https://software.sandia.gov/trac/coopr/wiki/GettingStarted for instructions for getting started with Coopr. Installers are available for MS Windows and Unix operating systems to simplify the installation of Coopr packages along with the third-party Python packages that they depend on. These installers can also automatically install extension packages from Coin Bazaar.

Enjoy!


About Coopr

Coopr is a collection of Python software packages that supports a diverse set of optimization capabilities for formulating and analyzing optimization models.

A key driver for Coopr development is Pyomo, an open source tool for modeling optimization applications in Python. Pyomo can be used to define symbolic problems, create concrete problem instances, and solve these instances with standard solvers. Thus, Pyomo provides a capability that is commonly associated with algebraic modeling languages like AMPL and GAMS.

Coopr 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.

Coopr development is hosted by Sandia National Laboratories and COIN-OR:

See  http://groups.google.com/group/coopr-forum/ for online discussions of Coopr.

  • Posted: 2011-11-11 15:08 (Updated: 2011-12-02 16:20)
  • Author: wehart
  • Categories: release

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