NIMBUS

class desdeo_mcdm.interactive.NIMBUS(problem, scalar_method=None)

Bases: desdeo_mcdm.interactive.InteractiveMethod.InteractiveMethod

Implements the synchronous NIMBUS algorithm.

Parameters

• problem (MOProblem) – The problem to be solved.

• scalar_method (Optional[ScalarMethod], optional) – The method used to solve the various ASF minimization problems present in the method. Defaults to None.

Methods Summary

calculate_new_solutions(number_of_solutions, …)	Calcualtes new solutions based on classifications supplied by the decision maker by
compute_intermediate_solutions(solutions, …)	Computs intermediate solution between two solutions computed earlier.
create_plot_request(objectives, msg)	Used to create a plot request for visualizing objective values.
handle_classification_request(request)	Handles a classification request.
handle_intermediate_solutions_request(request)	Handles an intermediate solutions request.
handle_most_preferred_request(request)	Handles a preferres solution request.
handle_save_request(request)	Handles a save request.
iterate(request)	Implements a finite state machine to iterate over the different steps defined in Synchronous NIMBUS based on a supllied request.
request_classification()	rtype Tuple[NimbusClassificationRequest, SimplePlotRequest]
request_most_preferred_solution(solutions, …)	Create a NimbusMostPreferredRequest.
request_stop()	Create a NimbusStopRequest based on self.
save_solutions_to_archive(objectives, …)	Save solutions to the archive.
start()	Return the first request to start iterating NIMBUS.
update_current_solution(solutions, …)	Update the state of self with a new current solution and the corresponding objective values.

Methods Documentation

calculate_new_solutions(number_of_solutions, levels, improve_inds, improve_until_inds, acceptable_inds, impaire_until_inds, free_inds)

Calcualtes new solutions based on classifications supplied by the decision maker by

solving ASF problems.

Parameters

• number_of_solutions (int) – Number of solutions, should be between 1 and 4.

• levels (np.ndarray) – Aspiration and upper bounds relevant to the some of the classifications.

• improve_inds (np.ndarray) – Indices corresponding to the objectives which should be improved.

• improve_until_inds (np.ndarray) – Like above, but improved until an aspiration level is reached.

• acceptable_inds (np.ndarray) – Indices of objectives which are acceptable as they are now.

• impaire_until_inds (np.ndarray) – Indices of objectives which may be impaired until an upper limit is reached.

• free_inds (np.ndarray) – Indices of objectives which may change freely.

Returns

A save request with the newly computed soutions, and a plot request to visualize said solutions.

Return type

Tuple[NimbusSaveRequest, SimplePlotRequest]

compute_intermediate_solutions(solutions, n_desired)

Computs intermediate solution between two solutions computed earlier.

Parameters

• solutions (np.ndarray) – The solutions between which the intermediat solutions should be computed.

• n_desired (int) – The number of intermediate solutions desired.

Raises

NimbusException –

Returns

A save request with the compured intermediate points, and a plot request to visualize said points.

Return type

Tuple[NimbusSaveRequest, SimplePlotRequest]

create_plot_request(objectives, msg)

Used to create a plot request for visualizing objective values.

Parameters

• objectives (np.ndarray) – A 2D numpy array containing objective vectors to be visualized.

• msg (str) – A message to be displayed in the context of a visualization.

Returns

A plot request to create a visualization.

Return type

SimplePlotRequest

handle_classification_request(request)

Handles a classification request.

Parameters

request (NimbusClassificationReuest) – A classification request with the response attribute set.

Returns

A NIMBUS save request and a plot request with the solutions the decision maker can choose from to save for alter use.

Return type

Tuple[NimbusSaveRequest, SimplePlotRequest]

handle_intermediate_solutions_request(request)

Handles an intermediate solutions request.

Parameters

request (NimbusIntermediateSolutionsRequest) – A NIMBUS intermediate solutions request with the response attribute set.

Returns

Return either a save request or a preferred solution request. The former is returned if the decision maker wishes to see intermediate points, the latter otherwise. Also a plot request is returned with the solutions available in it.

Return type

Tuple[Union[NimbusSaveRequest, NimbusMostPreferredRequest], SimplePlotRequest,]

handle_most_preferred_request(request)

Handles a preferres solution request.

Parameters

request (NimbusMostPreferredRequest) – A NIMBUS preferred solution request with the response attribute set.

Returns

Return a classificaiton request if the decision maker wishes to continue. If the decision maker wishes to stop, return a stop request. Also return a plot request with all the solutions saved so far.

Return type

Tuple[Union[NimbusClassificationRequest, NimbusStopRequest], SimplePlotRequest]

handle_save_request(request)

Handles a save request.

Parameters

request (NimbusSaveRequest) – A save request with the response attribute set.

Returns

Return an intermediate solution request where the decision maker can specify whether they would like to see intermediate solution between two previously computed solutions. The plot request has the available solutions.

Return type

Tuple[NimbusIntermediateSolutionsRequest, SimplePlotRequest]

iterate(request)

Implements a finite state machine to iterate over the different steps defined in Synchronous NIMBUS based on a supllied request.

Parameters

request (Union[NimbusClassificationRequest,NimbusSaveRequest,NimbusIntermediateSolutionsRequest,NimbusMostPreferredRequest,NimbusStopRequest,]) – A request based on the next step in the NIMBUS algorithm is taken.

Raises

NimbusException – If a wrong type of request is supllied based on the current state NIMBUS is in.

Returns

The next logically sound request.

Return type

Tuple[Union[NimbusClassificationRequest,NimbusSaveRequest,NimbusIntermediateSolutionsRequest,],Union[SimplePlotRequest, None],]

request_classification()

Return type

Tuple[NimbusClassificationRequest, SimplePlotRequest]

request_most_preferred_solution(solutions, objectives)

Create a NimbusMostPreferredRequest.

Parameters

• solutions (np.ndarray) – A 2D numpy array of decision variable vectors.

• objectives (np.ndarray) – A 2D numpy array of objective value vectors.

Returns

The requests based on the given arguments.

Return type

Tuple[NimbusMostPreferredRequest, SimplePlotRequest]

Note

The ‘i’th decision variable vector in solutions should correspond to the ‘i’th objective value vector in objectives.

request_stop()

Create a NimbusStopRequest based on self.

Returns

A stop request and a plot request with the final solution chosen in it.

Return type

Tuple[NimbusStopRequest, SimplePlotRequest]

save_solutions_to_archive(objectives, decision_variables, indices)

Save solutions to the archive. Saves also the corresponding objective function values.

Parameters

• objectives (np.ndarray) – Available objectives.

• decision_variables (np.ndarray) – Available solutions.

• indices (List[int]) – Indices of the solutions to be saved.

Returns

An intermediate solutions request asking the decision maker whether they would like to generate intermediata solutions between two existing solutions. Also returns a plot request to visualize the available solutions between which the intermediate solutions should be computed.

Return type

Tuple[NimbusIntermediateSolutionsRequest, None]

start()

Return the first request to start iterating NIMBUS.

Returns

The first request and and a plot request to visualize relevant data.

Return type

Tuple[NimbusClassificationRequest, SimplePlotRequest]

update_current_solution(solutions, objectives, index)

Update the state of self with a new current solution and the corresponding objective values. This solution is used in the classification phase of synchronous NIMBUS.

Parameters

• solutions (np.ndarray) – A 2D numpy array of decision variable vectors.

• objectives (np.ndarray) – A 2D numpy array of objective value vectors.

• index (int) – The index of the solution in solutions and objectives.

Returns

The requests based on the given arguments.

Return type

Tuple[NimbusMostPreferredRequest, SimplePlotRequest]

Note

The ‘i’th decision variable vector in solutions should correspond to the ‘i’th objective value vector in objectives.