The IBM Decision Optimization CPLEX Modeling for Python
Welcome to the IBM® Decision Optimization CPLEX Modeling for Python. Licensed under the Apache License v2.0.
With this library, you can quickly and easily add the power of optimization to your application. You can model your problems by using the Python API and solve them on the cloud with the IBM® Decision Optimization on Cloud service or on your computer with IBM® ILOG CPLEX Optimization Studio.
This library is composed of 2 modules:
- IBM® Decision Optimization CPLEX Optimizer Modeling for Python - with namespace docplex.mp
- IBM® Decision Optimization CP Optimizer Modeling for Python - with namespace docplex.cp
Solving with CPLEX locally requires that IBM® ILOG CPLEX Optimization Studio V12.6.3 or V12.7.0 is installed on your machine.
Solving with the IBM® Decision Optimization on Cloud service requires that you register for an account and get the API key.
This library is numpy friendly.
- pip install docplex
New in 1.0.630:
- Added support for CPLEX 12.7 and Python 3.5.
- Upgraded the DOcplexcloud client to version 1.0.202.
- Module docplex.mp.advmodel is now officially supported. This module
- provides support for efficient, specialized aggregator methods for large models.
- When solving on DOcplexcloud, proxies can now be specified with the
- context.solver.docloud.proxies property.
- When two constraints are defined with the same name, issue a warning instead of
- a fatal exception. The last constraint defined will take over the first one.
- Fix ValueError when passing a pandas DataFrame as variable keys (using
- DataFrame indexes).
- Solution.get_values() returns a collection of variables’ values in one call.
- docplex.mp.model no longer imports docloud.status. Any status
- previously initialized as JobSolveStatus.UNKNOWN is now initialized as None.
- Minor improvements to notebooks and examples.
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