Interface HardMediumSoftLongScoreHolder
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- All Superinterfaces:
ScoreHolder<HardMediumSoftLongScore>
- All Known Implementing Classes:
HardMediumSoftLongScoreHolderImpl
public interface HardMediumSoftLongScoreHolder extends ScoreHolder<HardMediumSoftLongScore>
- See Also:
HardMediumSoftLongScore
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Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description voidaddHardConstraintMatch(org.kie.api.runtime.rule.RuleContext kcontext, long hardWeight)voidaddMediumConstraintMatch(org.kie.api.runtime.rule.RuleContext kcontext, long mediumWeight)voidaddMultiConstraintMatch(org.kie.api.runtime.rule.RuleContext kcontext, long hardWeight, long mediumWeight, long softWeight)voidaddSoftConstraintMatch(org.kie.api.runtime.rule.RuleContext kcontext, long softWeight)voidimpactScore(org.kie.api.runtime.rule.RuleContext kcontext, long weightMultiplier)voidpenalize(org.kie.api.runtime.rule.RuleContext kcontext, long weightMultiplier)Penalize a match by theConstraintWeightnegated and multiplied with the weightMultiplier for all score levels.voidpenalize(org.kie.api.runtime.rule.RuleContext kcontext, long hardWeightMultiplier, long mediumWeightMultiplier, long softWeightMultiplier)Penalize a match by theConstraintWeightnegated and multiplied with the specific weightMultiplier per score level.voidreward(org.kie.api.runtime.rule.RuleContext kcontext, long weightMultiplier)Reward a match by theConstraintWeightmultiplied with the weightMultiplier for all score levels.voidreward(org.kie.api.runtime.rule.RuleContext kcontext, long hardWeightMultiplier, long mediumWeightMultiplier, long softWeightMultiplier)Reward a match by theConstraintWeightmultiplied with the specific weightMultiplier per score level.-
Methods inherited from interface org.optaplanner.core.api.score.holder.ScoreHolder
penalize, reward
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Method Detail
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penalize
void penalize(org.kie.api.runtime.rule.RuleContext kcontext, long weightMultiplier)Penalize a match by theConstraintWeightnegated and multiplied with the weightMultiplier for all score levels.- Parameters:
kcontext- never null, the magic variable in DRLweightMultiplier- at least 0
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penalize
void penalize(org.kie.api.runtime.rule.RuleContext kcontext, long hardWeightMultiplier, long mediumWeightMultiplier, long softWeightMultiplier)Penalize a match by theConstraintWeightnegated and multiplied with the specific weightMultiplier per score level. Slower thanpenalize(RuleContext, long).- Parameters:
kcontext- never null, the magic variable in DRLhardWeightMultiplier- at least 0mediumWeightMultiplier- at least 0softWeightMultiplier- at least 0
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reward
void reward(org.kie.api.runtime.rule.RuleContext kcontext, long weightMultiplier)Reward a match by theConstraintWeightmultiplied with the weightMultiplier for all score levels.- Parameters:
kcontext- never null, the magic variable in DRLweightMultiplier- at least 0
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reward
void reward(org.kie.api.runtime.rule.RuleContext kcontext, long hardWeightMultiplier, long mediumWeightMultiplier, long softWeightMultiplier)Reward a match by theConstraintWeightmultiplied with the specific weightMultiplier per score level. Slower thanreward(RuleContext, long).- Parameters:
kcontext- never null, the magic variable in DRLhardWeightMultiplier- at least 0mediumWeightMultiplier- at least 0softWeightMultiplier- at least 0
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impactScore
void impactScore(org.kie.api.runtime.rule.RuleContext kcontext, long weightMultiplier)
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addHardConstraintMatch
void addHardConstraintMatch(org.kie.api.runtime.rule.RuleContext kcontext, long hardWeight)- Parameters:
kcontext- never null, the magic variable in DRLhardWeight- higher is better, negative for a penalty, positive for a reward
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addMediumConstraintMatch
void addMediumConstraintMatch(org.kie.api.runtime.rule.RuleContext kcontext, long mediumWeight)- Parameters:
kcontext- never null, the magic variable in DRLmediumWeight- higher is better, negative for a penalty, positive for a reward
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addSoftConstraintMatch
void addSoftConstraintMatch(org.kie.api.runtime.rule.RuleContext kcontext, long softWeight)- Parameters:
kcontext- never null, the magic variable in DRLsoftWeight- higher is better, negative for a penalty, positive for a reward
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addMultiConstraintMatch
void addMultiConstraintMatch(org.kie.api.runtime.rule.RuleContext kcontext, long hardWeight, long mediumWeight, long softWeight)- Parameters:
kcontext- never null, the magic variable in DRLhardWeight- higher is better, negative for a penalty, positive for a rewardmediumWeight- higher is better, negative for a penalty, positive for a rewardsoftWeight- higher is better, negative for a penalty, positive for a reward
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