API

Graph

Attributes	col2
`Graph.structure`	Graph structur represented as a matrix of nodes separated by level
`Graph.actual_layer`	Represent the number of layers of de diagram

Methods	Description
`Graph.get_nodes_size()`	Representa la cantidad de nodos en el grafo
`Graph.add_node(Node)`	Add a node to the graph
`Graph.add_new_layer()`	Add a new layer to the graph
`Graph.remove_not_active_nodes_down_top(layer_index)`	Remove not active nodes in layer, construction bottom_up
`Graph.remove_not_active_nodes_top_down(layer_index)`	Remove not active nodes in layer, construction top_down

Attributes	Description
`DD.problem`	An instance of the problem class, used to create the decision diagram.

Methods	Description
`DD.create_decision_diagram(verbose) -> void`	Creates the initial decision diagram and records the time taken
`DD.create_reduce_decision_diagram(verbose) -> void`	Creates the reduced decision diagram and records the time taken.
`DD.create_restricted_decision_diagram(verbose) -> void`	Creates the restricted decision diagram and records the time taken
`DD.create_relaxed_decision_diagram(verbose) -> void`	Creates the relaxed decision diagram and records the time taken.
`DD.print_decision_diagram()->str`	Prints the decision diagram for visualization, noting the limitation of a maximum of 4 different line types.
`DD.export_graph_file(file_name)->void`	Exports the current decision diagram to a .GML file.
`DD.get_decision_diagram_graph()-> Graph`	Returns the current decision diagram graph object
`DD.get_decision_diagram_graph_copy()-> Graph`	Returns a copy of the decision diagram graph object, ensuring it is not a pointer to the original.
`DD.get_dd_builder_time()->void`	Returns the execution time of the DDBuilder.
`DD.get_reduce_dd_builder_time()->void`	Returns the execution time of the reduce constructor.
`DD.get_restricted_dd_builder_time()->void`	Returns the execution time of the restricted constructor.
`DD.get_relaxed_dd_builder_time()->void`	Returns the execution time of the relaxed constructor.

Attributes	Description
`ObjectiveFunction.graph_DD`	The decision diagram graph to be solved.
`ObjectiveFunction.time`	Time taken to solve the decision diagram.
`ObjectiveFunction.answer`	Structure that stores the solution of the objective function

Methods	Description
`ObjectiveFunction.set_objective_function(objective_function)->void`	Stores the necessary information to define an objective function.
`ObjectiveFunction.solve_dd()->AnswerStructure`	Solves the decision diagram, returning the optimal solution.
`ObjectiveFunction.get_time() -> str`	Returns the execution time of the solving algorithm.
`ObjectiveFunction.get_the_solution -> AnswerStructure`	Returns the precomputed solution from solve_dd().

Attributes	Description
`problem.initial_state`	The initial state of the problem, which can be a list, integer, string, etc., depending on the specific problem requirements
`problem.ordered_variables`	A list of variables sorted in the specific order that was given.
`problem.variables_domain`	A dictionary mapping each variable to its domain.

Methods	Description
`problem.equals(State state_one, State state_two) -> bool`	Abstract method that must be implemented by subclasses to determine if two states are equal.
`problem.transition_function(previus_state, variable_id, variable_value) -> (State state, bool feasibility)`	Abstract method that must be implemented by subclasses to define the transition function.
`problem.get_priority_for_discard_node(state) -> int value`	Method that should be implemented by subclasses to define the priority function for discarding nodes.
`problem.get_priority_for_merge_nodes(node_id, state) -> int value`	Method that should be implemented by subclasses to define the priority function for merging nodes.
`problem.merge_operator(state_one, state_two) -> State state`	Method that should be implemented by subclasses to define the new state when two nodes are merged
`problem.get_state_as_string(state) -> string state`	Method that should be implemented by subclasses to define a string representation of the state.

Methods	Description
`MaxFlow.get_time() -> double`	Returns the execution time of the max-flow algorithm.
`MaxFlow.get_max_flow() -> double`	Returns the precomputed values in the solve_max_flow() section.
`MaxFlow.get_remaining_arcs_capacities() -> unordered_map<string, double>`	Returns the remaining capacities of the arcs in the graph.
`MaxFlow.solve_max_flow(capacities) -> bool`	Solves the maximum flow problem in the graph with the provided arc capacities. Returns a boolean indicating whether the solution was successfully found.

Methods	Description
`Cut.get_time() -> double`	Returns the execution time of the cut algorithm.
`Cut.get_cut() -> pair<vector<double, double>>`	Returns the precomputed values from the generate_cut() method.
`Cut.generate_cut(x_values, verbose) -> bool`	Solves the decision diagram, finding a cut. Returns a boolean indicating whether the solution was successfully found.

col1	Description
`LiftCut.get_time() -> double`	Returns the execution time of the lift algorithm.
`LiftCut.get_lift_cut() -> pair<vector<double, double>>`	Returns the precomputed values from the lift_cut() method.
`LiftCut.lift_cut(coeficcients, constant) -> bool`	Lifts the cut by improving the coefficients and right-hand side value. Returns a boolean indicating whether the solution was successfully found.