Package ai.timefold.solver.core.impl.exhaustivesearch.node.bounder

Class TrendBasedScoreBounder

java.lang.Object

ai.timefold.solver.core.impl.exhaustivesearch.node.bounder.TrendBasedScoreBounder

All Implemented Interfaces:

ScoreBounder

public class TrendBasedScoreBounder
extends Object
implements ScoreBounder

Field Summary

Fields

Modifier and Type	Field	Description
protected final InitializingScoreTrend	initializingScoreTrend
protected final ScoreDefinition	scoreDefinition

Constructor Summary

Constructors

Constructor	Description
TrendBasedScoreBounder(ScoreDefinition scoreDefinition, InitializingScoreTrend initializingScoreTrend)

Method Summary

Modifier and Type	Method	Description
Score	calculateOptimisticBound(ScoreDirector scoreDirector, Score score)	In OR terms, this is called the lower bound if they minimize, and upper bound if they maximize.
Score	calculatePessimisticBound(ScoreDirector scoreDirector, Score score)	In OR terms, this is called the upper bound if they minimize, and lower bound if they maximize.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

scoreDefinition

protected final ScoreDefinition scoreDefinition

initializingScoreTrend

protected final InitializingScoreTrend initializingScoreTrend

Constructor Details

TrendBasedScoreBounder

public TrendBasedScoreBounder(ScoreDefinition scoreDefinition,
 InitializingScoreTrend initializingScoreTrend)

Method Details

calculateOptimisticBound

public Score calculateOptimisticBound(ScoreDirector scoreDirector,
 Score score)

Description copied from interface: ScoreBounder

In OR terms, this is called the lower bound if they minimize, and upper bound if they maximize. Because we always maximize the Score, calling it lower bound would be a contradiction.

Specified by:

calculateOptimisticBound in interface ScoreBounder

Parameters:

scoreDirector - never null, use ScoreDirector.getWorkingSolution() to get the working PlanningSolution

score - never null, the Score of the working PlanningSolution

Returns:

never null, never worse than the best possible Score we can get by initializing the uninitialized variables of the working PlanningSolution.

See Also:

• ScoreDefinition.buildOptimisticBound(InitializingScoreTrend, Score)

calculatePessimisticBound

public Score calculatePessimisticBound(ScoreDirector scoreDirector,
 Score score)

Description copied from interface: ScoreBounder

In OR terms, this is called the upper bound if they minimize, and lower bound if they maximize. Because we always maximize the Score, calling it upper bound would be a contradiction.

Specified by:

calculatePessimisticBound in interface ScoreBounder

Parameters:

scoreDirector - never null, use ScoreDirector.getWorkingSolution() to get the working PlanningSolution

score - never null, the Score of the working PlanningSolution

Returns:

never null, never better than the worst possible Score we can get by initializing the uninitialized variables of the working PlanningSolution.

See Also:

• ScoreDefinition.buildPessimisticBound(InitializingScoreTrend, Score)