Docplex

* Both ``docplex.mp`` & ``docplex.cp``:
* Support for CPLEX engines 12.8. Some features of docplex2.4 are available only with engines >= 12.8.
* Adding new ports (AIX, plinux).
* Examples are now available as Zeppelin notebooks.

* In ``docplex.mp``:
* Express a linear problem as a scikit-learn transformer by providing a numpy, a pandas or scipy matrix.
* Logical constraints: constraint equivalence, if-then & rshift operator.
* Meta-constraints: allow the use of discrete
linear constraints in expressions, using their truth value.
* Solve hook to add a method to be called at each intermediate solution.
* KPIS automatically published at each intermediate solution if running on docplexcloud python worker.
* Support for scipy coo & csr matrixes.
* Fixed a bug in Model.add_constraints() when passing a string instead of a list of strings.

* In ``docplex.cp``:
* add new method run_seeds() to execute a model multiple times, available with local solver 12.8.
* add support of new solver infos 'SearchStatus' and 'SearchStopCause'.
* In method ``docplex.cp.model.CpoModel.propagate()``, add possibility to add an optional constraint to the model.
* add domain iterator in integer variables and integer variables solutions, allowing to get domain
as a list of individual integers.
* add possibility to identify some model variables as KPIs of the model.
* add abort_search() method on solver (not supported everywhere)
* Rework code generation to enhance performances and remove unused variables that was pointed by removed expressions.
* add possibility to add one or more CpoSolverListener to put some callback functions
when solve is started, ended, or when a solution is found.
Implementation is provided in new python module ``docplex.cp.solver.solver_listener`` that also contains sample
listeners SolverProgressPanelListener and AutoStopListener.
* Using parameter *context.solver.solve_with_start_next*, enable solve() method to execute a start/next loop instead
of standard solve. This enables, for optimization problems, usage of SolveListeners with a greater progress accuracy.
* Completely remove deprecated 'angel' to identify local solver.
* Deprecate usage of methods ``minimize()`` and ``maximize()`` on ``docplex.cp.CpoModel``.
* Add methods ``get_objective_bounds()`` and ``get_objective_gaps()`` in solution objects.

* Module ``docplex.cp.model.solver_angel.py`` has been renamed ``solver_local.py``.
A shadow copy with previous name still exist to preserve ascending compatibility.
Module ``docplex.cp.model.config.py`` is modified to refer this new module.
* Class ``docplex.cp.model.solver_local.SolverAngel`` has been renamed ``SolverLocal``.
A shadow copy with previous name still exist to preserve ascending compatibility.
* Class ``docplex.cp.model.solver_local.AngelException`` has been renamed ``LocalSolverException``.
A shadow copy with previous name still exist to preserve ascending compatibility.
* Functions logical_and() and logical_or() are able to accept a list of model boolean expressions.
* Fix defect on allowed_assignments() and forbiden_assignments() that was wrongly converting
list of tupes into tuple_set.
* Update all examples to add comments and split them in sections data / prepare / model / solve
* Add new sched_RCPSPMM_json.py example that reads data from JSON file instead of raw data file.
* Rename all visu examples with more explicit names.
* Remove the object class CpoTupleSet. Tuple sets can be constructed only by calling tuple_set() method, or more
simply by passing directly a Python iterable of iterables when a tupleset is required
(in expressions allowed_assignments() and forbidden_assignments)
* Allow logical_and() and logical_or() to accept a list of boolean expressions.
* Add overloading of builtin functions all() and any() as other form of logical_and() and logical_or().
* In no_overlap() and state_function(), transition matrix can be passed directly as a Python iterable of iterables of integers,
* Editable transition matrix, created with a size only, is deprecated. However it is still available for ascending compatibility.
* Add conditional() modeling function
* Parameter 'AutomaticReplay' is deprecated.
* Add get_search_status() and get_stop_cause() on object CpoSolveResult, available for solver COS12.8
* Improved performance of ``Var.reduced_cost()`` in ``docplex.mp``.

* Methods ``docplex.cp.model.export_model()`` and ``docplex.cp.model.import_model()``
have been added to respectively generate or parse a model in CPO format.
* Methods ``docplex.cp.model.minimize()`` and ``docplex.cp.model.maximize()``
have been added to directly indicate an objective at model level.
* Notebook example ``scheduling_tuto.ipynb`` contains an extensive tutorial
to solve scheduling problems with CP.
* Modeling method sum() now supports sum of cumul expressions.
* Methods ``docplex.cp.model.start_search()`` allows to start a new
search sequence directly from the model object.
* When setting ``context.solver.auto_publish`` is set, and using the CPLEX
engine, KPIs and current objective are automatically published when the
script is run on DOcplexcloud Python worker.
* When setting ``context.solver.auto_publish`` is set, and using the CP
engine, current objective is automatically published when the
script is run on DOcplexcloud Python worker.
* ``docplex.util.environment.Environment.set_stop_callback`` and
``docplex.util.environment.Environment.get_stop_callback`` are added so that
you can add a callback when the DOcplexcloud job is aborted.

* In ``docplex.cp``: robustify the handling of callback messages coming from CP Optimizer
* Allows to use numpy 2.0

* New methods ``Model.logical_or()`` and ``Model.logical_and()`` handle
logical operations on binary variables.
* DOcplex now supports CPLEX 12.7.1 and Benders decomposition. Set annotations
on constraints and variables using the ``benders_annotation`` property and use
the proper CPLEX parameters governing Benders decomposition.
* CPLEX tutorials: in the documentation and as notebooks in the examples.
* Fixed a bug in ``docplex.mp.solution.SolveSolution.display()`` and in
``docplex.mp.solution.Model.report_kpi()`` when using unicode variable names.
* There's now a simple command line interface for DOcplexcloud. It can be run
in a terminal. ``python -m docplex.cli help`` for more info. That command
line reads your DOcplexcloud credentials in your cplex_config.py file. It
allows you to submit, list, delete jobs on DOcplexcloud. The cli is available
in notebooks too, using the ``%docplex_cli`` magics. ``%docplex_cli help`` for
some help. In a notebook, credentials can be passed using `%docplex_url` and
`%docplex_key` magics.
* Removing constraints in 1 call
* Bug fixes when editing an existing model.
* Bug fix in the relaxation mechanism when using docplexcloud.

* Piecewise linear (PWL) functions are now supported. An API is now available
on ``docplex.mp.model`` to create PWL functions and to create constraints using these PWL functions.
PWL functions may be defined with breakpoints (default API) or by using slopes. Some simple arithmetic is
also available to build new PWL functions by adding, subtracting, or scaling existing PWL functions.
* DOcplex has undergone a significant overhaul effort that has resulted in an average of 30-50% improvement
of modeling run-time performance. All parts of the API benefit from the performance improvements: creation of variables and constraints, removal of constraints, computation of sums of variables, and so on.
* Constraints are now fully editable:
the expressions of a constraint can be modified.
Similarly, the objective expression can also be modified. This allows for complex workflows in which the model is modified after a solve and then solved again.
* docplex is now available on Anaconda cloud and can be installed via the conda installation packager.
See the `IBM Anaconda home <https://anaconda.org/IBMDecisionOptimization>`_
CPLEX Community Edition for Python is also provided on Anaconda Cloud to get free local solving capabilities with limitations.
* Support of ``~/.docplexrc`` configuration files for ``docplex.mp.context.Context`` is now dropped.
This feature has been deprecated since 1.0.0.
* Known incompatibility: class ``docplex.mp.model.AbstractModel`` moved to ``docplex.mp.absmodel.AbstractModel``.
Samples using this class have been updated.