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Globalizer
==========
Globalizer [1]_ analyses a model and set of data to provide suggestions of
global constraints that can replace or enhance a user's model.
Basic Usage
-----------
To use Globalizer simply execute it on a model and set of data files:
``minizinc --solver org.minizinc.globalizer model.mzn data-1.dzn data-2.dzn``
Note: Globalizer may also be executed on a non-parameterised model with
no data files.
The following demonstrates the basic usage of Globalizer.
Below, we see a simple model for the car sequencing problem [2]_, ``cars.mzn``.
.. literalinclude:: examples/cars.mzn
:language: minizinc
:name: ex-glob-cars
:caption: Model for the car sequencing problem (:download:`cars.mzn <examples/cars.mzn>`).
And here we have a data file ``cars_data.dzn``.
.. literalinclude:: examples/cars_data.dzn
:language: minizinc
:name: ex-glob-cars-data
:caption: Data for the car sequencing problem (:download:`cars_data.dzn <examples/cars_data.dzn>`).
Executing Globalizer on this model and data file we get the following output:
.. code-block:: minizincdef
% minizinc --solver globalizer cars.mzn cars_data.dzn
cars.mzn|33|12|33|69 [ ] gcc(class,cars_in_class)
cars.mzn|33|35|33|68 [ ] count(class,c,cars_in_class[c])
cars.mzn|28|27|28|65;cars.mzn|29|9|30|32 [ ] sliding_sum(0,max_per_block[p],block_size[p],used[_, p])
Each line of output is comprised of three elements.
#. Expression locations (separated by semicolon ';') that the constraint might be able to replace.
#. (Between square brackets '[' ']') the context under which the constraint might replace the expressions of 1.
#. The replacement constraint.
From the example above we see that a ``gcc`` constraint and a ``sliding_sum``
constraint can replace some constraints in the model. Taking the ``sliding_sum``
case, we see that it replaces the expression ``cars.mzn|28|27|28|65`` which
corresponds to ``i in 1..(n_cars - (block_size[p] - 1))`` and ``cars.mzn|29|27|28|65``
which corresponds to the ``<=`` expression including the ``sum``.
The original constraint can be replaced with:
.. code-block:: minizincdef
constraint forall (p in options) (
sliding_sum(0, max_per_block[p], block_size[p], used[..,p]));
Caveats
-------
**MiniZinc syntax support.**
Globalizer was implemented with support for a subset of an early version
of the MiniZinc 2.0 language. As a result there are some limitations.
First, Globalizer does not support ``set`` variables or ``enum`` types.
The array slicing syntax supported in MiniZinc was not decided upon when
Globalizer was implemented so it uses an incompatible syntax. Globalizer
uses ``_`` instead of ``..``. This can be seen above in the translation
of ``used[_,p]`` to ``used[..,p]``.
**New constraint.**
A special two argument version of the ``global_cardinality`` constraint
called ``gcc`` has been added which is not in the standard library. It is
defined as follows:
.. code-block:: minizincdef
predicate gcc(array[int] of var int: x, array[int] of var int: counts) =
global_cardinality(x,
[ i | i in index_set(counts) ],
array1d(counts));
Supported Constraints
---------------------
Globalizer currently supports detection of the following constraints:
.. code-block:: minizincdef
alldifferent alldifferent_except_0 all_equal_int
bin_packing bin_packing_capa bin_packing_load
binaries_represent_int binaries_represent_int_3A binaries_represent_int_3B
binaries_represent_int_3C channel channelACB
count_geq cumulative_assert decreasing
gcc global_cardinality inverse
lex_lesseq_int_checking lex2_checking maximum_int_checking
minimum_int_checking member nvalue
strict_lex2_checking subcircuit_checking true
atleast atmost bin_packing_load_ub
circuit_checking count diffn
distribute element increasing
lex_less_int_checking sliding_sum sort_checking
unary value_precede_checking
Using Globalizer in the MiniZinc IDE
------------------------------------
To use the Globalizer in the MiniZinc IDE, open a model, and several
data files.
Select ``Globalizer`` from the solver configuration dropdown menu.
Click the solve button (play symbol).
If you did not select any data file, a dialog should pop up that allows
you to select data files.
To select multiple data files hold the ``Ctrl`` or ``Cmd`` key while
clicking on each data file.
.. image:: figures/globalizer/ide_select_data.png
Click run. While processing your model and data files the MiniZinc IDE
will display a progress bar on the toolbar.
.. image:: figures/globalizer/ide_globalized.png
Any discovered global constraints will be listed in the output pane
of the IDE. Clicking on one of these constraints will highlight in the
model the expressions that might be replaceable or strengthened by the
constraint.
How it works
------------
A summary of the algorithm is presented here. For a more detailed
exploration of the approach see the Globalizing Constraint Models paper [1]_.
- **Normalize.**
In this step the model is transformed to make analysis easier.
- Conjunctions of constraints are broken into individual constraints.
For example: ``C1 /\ C2;`` becomes ``C1; C2``;
- Conjunctions under ``forall`` constraints are broken into individual
``forall`` constraints. For example: ``forall(...) (C1 /\ C2);``
becomes ``forall(...) (C1); forall(...) (C2)``
- **Generate submodels.**
In this step all subsets containing 1 or 2 constraints (this can be
configured using ``--numConstraints`` argument) are enumerated.
- **Instantiate and unroll into groups.**
Each submodel is instantiated with the provided data files. These
instantiated submodels are further used to produce more submodels
by unrolling loops. For example, a constraint such as
``forall(i in 1..n) (c(i));`` will be used to produce the constraints:
``c(1)`` and ``c(n)`` for each instantiation of n in the data files.
All instantiated submodels are then grouped together.
- **Process groups.**
For each submodel in a group a set of 30 random solutions are found.
(configurable using the ``--randomSolutions`` argument).
A template model with all of these random solutions is created.
The different variables (including arrays and array accesses) and
parameters used by a submodel are collected into a set of potential
arguments along with the constant 0 and a special blank symbol
representing an argument that can be inferred based on others used.
The list of constraints above is filtered based on the arguments
available. For example, the ``alldifferent`` constraint will
be removed from the list of candidates if the submodel does not
reference any arrays of variables.
Finally the set of constraints are filtered by adding them to the
template and solving it. If the template is satisfiable, the
constraint accepts all of the random solutions.
30 sample solutions for each candidate constraint are generated.
(configurable using the ``--sampleSolutions`` argument).
The candidate is then ranked based on how many of these solutions
are also solutions to the original submodel. If its score is less
than some threshold the candidate is removed from the set of
candidates for this group and will not be tested on later
submodels.
- **Report.**
The remaining candidates are presented to the user.
Performance tips
----------------
Globalizing constraint models can be a time consuming task. If
- **Use small or relatively easy instances.**
Globalizer solves many subproblems while processing your model and data files. Using easier instances can speed up the process considerably.
- **Disable the initial pass.**
As discussed above, Globalizer performs two passes. The first pass tries to detect alternate viewpoints that can be added to your model. If you are confident that this will not be useful we recommend disabling this first pass using the ``--no-initial-pass`` argument.
- **Narrow search using filters.**
Globalizer attempts to match a large selection of global constraints to subproblems in your model.
If you wish to check if only a few specific constraints are present you can focus Globalizer using the ``--constraintFilter`` or ``-f`` arguments followed by a comma separated list of strings.
Only global constraints where one of the strings is a substring will be included in the search.
- **Disable implies check.**
The implication check can also be disabled to improve performance. This results in less accurate results but may still help a user to understand the structure of their model.
- **Free-search.**
To improve accuracy and to avoid false positives, subproblems solved by Globalizer are solved using a random heuristic and restarts. If the subproblems are particularly difficult to solve a random heuristic may be prohibitive and the solver may not be able to produce enough samples within the solving timelimit.
In these circumstances a user can either increase the solver timeout using the ``-t`` argument followed by the number of milliseconds a solver should be given to find samples.
Alternatively the ``--free-search`` argument can be used to force Globalizer to use the solver's free search to find samples.
This has the downside of reducing the diversity of samples but allows enough samples to be found to allow suggested globals to be found.
Limitations / Future work
-------------------------
- Globalizer supports only a subset of the MiniZinc language and as such
cannot be executed on all MiniZinc models.
- There are some relatively cheap syntactic approaches that should
be performed before Globalization that currently is not implemented.
For example, there are several common formulations of an ``alldifferent``
constraint that can be detected syntactically. This would be much
cheaper than using Globalizer.
.. [1] Leo, K. et al., "Globalizing Constraint Models", 2013.
.. [2] http://www.csplib.org/Problems/prob001/