Model

Constructor

Model(**kwargs)

Creates an optimization model

Components

Model.get_name(self)	Returns model name
Model.set_session(self, session)	Sets the session of model
Model.get_session(self)	Returns the session of the model
Model.get_session_type(self)	Tests whether the model session is defined and still active
Model.set_objective(self, expression, name)	Specifies the objective function for the model
Model.append_objective(self, expression, name)	Appends a new objective to the model
Model.get_objective(self)	Returns the objective function as an Expression object
Model.get_all_objectives(self)	Returns a list of objectives in the model
Model.add_variable(self, name[, vartype, …])	Adds a new variable to the model
Model.add_variables(self, \*argv, name[, …])	Adds a group of variables to the model
Model.add_implicit_variable(self[, argv, name])	Adds an implicit variable to the model
Model.get_variable(self, name)	Returns the reference to a variable in the model
Model.get_variables(self)	Returns a list of variables
Model.get_grouped_variables(self)	Returns an ordered dictionary of variables
Model.get_implicit_variables(self)	Returns a list of implicit variables
Model.get_variable_coef(self, var)	Returns the objective value coefficient of a variable
Model.drop_variable(self, variable)	Drops a variable from the model
Model.drop_variables(self, \*variables)	Drops a variable group from the model
Model.add_constraint(self, c, name)	Adds a single constraint to the model
Model.add_constraints(self, argv, name)	Adds a set of constraints to the model
Model.get_constraint(self, name)	Returns the reference to a constraint in the model
Model.get_constraints(self)	Returns a list of constraints in the model
Model.get_grouped_constraints(self)	Returns an ordered dictionary of constraints
Model.drop_constraint(self, constraint)	Drops a constraint from the model
Model.drop_constraints(self, \*constraints)	Drops a constraint group from the model
Model.add_set(self, name[, init, value, settype])	Adds a set to the model
Model.add_parameter(self, \*argv, name[, …])	Adds a abstract.Parameter object to the model
Model.add_statement(self, statement[, …])	Adds a PROC OPTMODEL statement to the model
Model.get_sets(self)	Returns a list of Set objects in the model
Model.get_parameters(self)	Returns a list of abstract.Parameter and abstract.ParameterGroup objects in the model
Model.get_statements(self)	Returns a list of all statements inside the model
Model.include(self, \*argv)	Adds existing variables and constraints to a model

Solver calls

Model.solve(self, \*\*kwargs)	Solves the model by calling CAS or SAS optimization solvers
Model.tune_parameters(self, \*\*kwargs)	Tunes the model to find ideal solver parameters
Model.get_solution(self[, vtype, solution, …])	Returns the primal and dual problem solutions
Model.get_variable_value(self, var)	Returns the value of a variable
Model.get_objective_value(self)	Returns the optimal objective value
Model.get_solution_summary(self)	Returns the solution summary table to the user
Model.get_problem_summary(self)	Returns the problem summary table to the user
Model.get_tuner_results(self)	Returns the tuning results
Model.print_solution(self)	Prints the current values of the variables
Model.clear_solution(self)	Clears the cached solution of the model

Export

Model.to_mps(self, \*\*kwargs)	Returns the problem in MPS format
Model.to_optmodel(self, \*\*kwargs)	Returns the model in OPTMODEL format
Model.export_mps(self[, filename, fetch])	Exports model in MPS format

Internal functions

Model._is_linear(self)

Checks whether the model can be written as a linear model (in MPS format)

Deprecated

Deprecated since version 1.0.0.

The following method(s) are deprecated and will be removed in future minor updates.

Model.to_frame(self, \*\*kwargs)