Package ai.timefold.solver.core.api.solver

Interface RecommendedAssignment<Proposition_,Score_ extends Score<Score_>>

Type Parameters:

Proposition_ - the generic type of the proposition as returned by the proposition function

Score_ - the generic type of the score

All Known Subinterfaces:

RecommendedFit<Proposition_,Score_>

All Known Implementing Classes:

DefaultRecommendedAssignment, DefaultRecommendedFit

public interface RecommendedAssignment<Proposition_,Score_ extends Score<Score_>>

Represents the result of the Assignment Recommendation API, see SolutionManager.recommendFit(Object, Object, Function).

In order to be fully serializable to JSON, propositions must be fully serializable to JSON. For deserialization from JSON, the user needs to provide the deserializer themselves. This is due to the fact that, once the proposition is received over the wire, we no longer know which type was used. The user has all of that information in their domain model, and so they are the correct party to provide the deserializer. See also ScoreAnalysis Javadoc for additional notes on serializing and deserializing that type.

Method Summary

Modifier and Type	Method	Description
@Nullable Proposition_	proposition()	Returns the proposition as returned by the proposition function.
@NonNull ScoreAnalysis<Score_>	scoreAnalysisDiff()	Difference between the original score and the score of the solution with the recommendation applied.

Method Details

proposition

@Nullable Proposition_ proposition()

Returns the proposition as returned by the proposition function. This is the actual assignment recommended to the user.

Returns:

null if proposition function required null

scoreAnalysisDiff

@NonNull ScoreAnalysis<Score_> scoreAnalysisDiff()

Difference between the original score and the score of the solution with the recommendation applied.

If SolutionManager.recommendAssignment(Object, Object, Function, ScoreAnalysisFetchPolicy) was called with ScoreAnalysisFetchPolicy.FETCH_ALL, the analysis will include constraint matches inside its constraint analysis; otherwise it will not.

Returns:

fittedScoreAnalysis - originalScoreAnalysis as defined by ScoreAnalysis.diff(ScoreAnalysis)