org.optaplanner.core.impl.exhaustivesearch.node.bounder
Class TrendBasedScoreBounder
java.lang.Object
org.optaplanner.core.impl.exhaustivesearch.node.bounder.TrendBasedScoreBounder
- All Implemented Interfaces:
- ScoreBounder
public class TrendBasedScoreBounder
- extends Object
- implements ScoreBounder
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
scoreDefinition
protected final ScoreDefinition scoreDefinition
initializingScoreTrend
protected final InitializingScoreTrend initializingScoreTrend
TrendBasedScoreBounder
public TrendBasedScoreBounder(InnerScoreDirectorFactory scoreDirectorFactory)
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 Solution
score
- never null, the Score
of the working Solution
- Returns:
- never null, never worse than the best possible
Score
we can get
by initializing the uninitialized variables of the working Solution
.
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 Solution
score
- never null, the Score
of the working Solution
- Returns:
- never null, never better than the worst possible
Score
we can get
by initializing the uninitialized variables of the working Solution
.
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