Model (cpmpy.Model)
The Model class is a lazy container for constraints and an objective function.
It is lazy in that it only stores the constraints and objective that are added to it. Processing only starts when solve() is called, and this does not modify the constraints or objective stored in the model.
A model can be solved multiple times, and constraints can be added to it inbetween solve calls.
See the examples for basic usage, which involves:
creation, e.g. m = Model(cons, minimize=obj)
solving, e.g. m.solve()
optionally, checking status/runtime, e.g. m.status()
List of classes
CPMpy Model object, contains the constraint and objective expressions |
- class cpmpy.model.Model(*args, minimize=None, maximize=None)[source]
CPMpy Model object, contains the constraint and objective expressions
- copy()[source]
Makes a shallow copy of the model. Constraints and variables are shared among the original and copied model (references to the same Expression objects). The /list/ of constraints itself is different, so adding or removing constraints from one model does not affect the other.
- static from_file(fname)[source]
Reads a Model instance from a binary pickled file
- Returns:
an object of :class: Model
- maximize(expr)[source]
Maximize the given objective function
maximize() can be called multiple times, only the last one is stored
- minimize(expr)[source]
Minimize the given objective function
minimize() can be called multiple times, only the last one is stored
- objective(expr, minimize)[source]
Post the given expression to the solver as objective to minimize/maximize
expr: Expression, the CPMpy expression that represents the objective function
minimize: Bool, whether it is a minimization problem (True) or maximization problem (False)
‘objective()’ can be called multiple times, only the last one is stored
- objective_value()[source]
Returns the value of the objective function of the latste solver run on this model
- Returns:
an integer or ‘None’ if it is not run, or a satisfaction problem
- solve(solver=None, time_limit=None, **kwargs)[source]
Send the model to a solver and get the result
- Parameters:
solver – name of a solver to use. Run SolverLookup.solvernames() to find out the valid solver names on your system. (default: None = first available solver)
time_limit (int or float) – optional, time limit in seconds
- Returns:
Bool: the computed output: - True if a solution is found (not necessarily optimal, e.g. could be after timeout) - False if no solution is found
- solveAll(solver=None, display=None, time_limit=None, solution_limit=None)[source]
Compute all solutions and optionally display the solutions.
Delegated to the solver, who might implement this efficiently
- Arguments:
- display: either a list of CPMpy expressions, OR a callback function, called with the variables after value-mapping
default/None: nothing displayed
solution_limit: stop after this many solutions (default: None)
Returns: number of solutions found