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Acceptor.Terminations.CountableValueRange (and therefore ValueRange).DeciderScoreComparatorFactory.EntityPlacer.EntitySelector.FeasibilityScoreDefinition.FinalistPodium.Forager.IncrementalScoreCalculator.MoveMoveSelector.Score.ScoreDefinition.ScoreDirector.ScoreDirectorFactory.ScoreHolder.Selector.Termination.ValueRange that is not a CountableValueRange).ValueSelector.Forager which forages accepted moves and ignores unaccepted moves.Move.SingleBenchmarkResult.accumulateResults(BenchmarkReport),
because PlannerBenchmarkResult.accumulateResults(BenchmarkReport) does that already on
PlannerBenchmarkResult.getUnifiedProblemBenchmarkResultList().
Forager.addMove(LocalSearchMoveScope).
ProblemFactChange to be processed.
BasicPlumbingTermination.waitForRestartSolverDecision()
Score is calculated for the current workingSolution
in the current ScoreDirector (with possibly incremental calculation residue),
it is equal to the parameter expectedWorkingScore.
Score is calculated for the parameter solution,
it would be equal to the Solution.getScore() of that parameter.
Score is calculated for the current workingSolution
in a fresh ScoreDirector (with no incremental calculation residue),
it is equal to the parameter workingScore.
BasicPlumbingTermination.problemFactChangeQueue is not empty or BasicPlumbingTermination.terminatedEarly is true)Score is based on n levels of BigDecimal constraints.Score is based on n levels of int constraints.Solution is found.
Solution changes during solving.Solver encounters.BigDecimal.scale().
BigDecimal.scale().
Score which is equal or better than any other Score with more variables initialized
(while the already variables don't change).
Score which is equal or worse than any other Score with more variables initialized
(while the already variables don't change).
PlannerBenchmark instance.
InnerScoreDirectorFactory.buildScoreDirector(), but optionally disables ConstraintMatch tracking
for more performance (presuming the ScoreDirector implementation actually supports it to begin with).
ScoreDirector instance.
DroolsScoreDirector.
Solver instance.
XStream setup which is used to read/write solver configs and benchmark configs.
Iterator does not shuffle and is never ending.EntitySelector that caches the result of its child EntitySelector.MoveSelector that caches the result of its child MoveSelector.ValueSelector that caches the result of its child ValueSelector.Termination.calculateSolverTimeGradient(DefaultSolverScope).
Score and updates the workingSolution accordingly.
CompositeMoveSelector that cartesian products 2 or more MoveSelectors.ScoreDirector and its workingSolution.
ConstraintMatch list
by ConstraintMatch.getJustificationList().
ConstraintMatch list
by ConstraintMatch.getJustificationList().
ConstraintMatch list
by ConstraintMatch.getJustificationList().
ConstraintMatch list
by ConstraintMatch.getJustificationList().
MoveSelector.IncrementalScoreCalculator to report ConstraintMatchTotals
for explaining a score (= which score constraints match for how much)
and also for score corruption analysis.ConstructionHeuristicPhase is a Phase which uses a construction heuristic algorithm,
such as First Fit, First Fit Decreasing, Cheapest Insertion, ...AbstractCountableValueRange
to ensure backwards compatibility in future versions.BigDecimal.scale().
BigDecimal.scale().
SelectionCacheType.
SelectionCacheType.
SelectionCacheType.
Solver.
CustomPhase is a Phase which uses the brute force algorithmPlanningVariable's.ConstructionHeuristicPhase.CustomPhase.ExhaustiveSearchPhase.LocalSearchPhase.PropertyDescriptor for faster and easier access.Solver.SubChainSelector implementation.Solution of the ScoreDirector
and notifies the ScoreDirector accordingly.
Solution and its ScoreDirector accordingly.
ScoreDirector, which directs the Rule Engine to calculate the Score
of the Solution workingSolution.ScoreDirectorFactory.Score calculation.ScoreDirector, which recalculates the Score
of the Solution workingSolution every time.ScoreDirectorFactory.Selector.isNeverEnding() is true, then Iterable.iterator() will never end.
QueuedEntityPlacerConfig and PooledEntityPlacerConfig.PlanningEntity annotated class.PlanningEntity instances.ProblemBenchmarksConfig.buildProblemBenchmarkList(SolverBenchmarkResult).
ExhaustiveSearchPhase is a Phase which uses an exhaustive algorithm.Score, calculated by the KieSession for DroolsScoreDirector.
ValueRangeDescriptor.extractValueRange(Solution, Object).
Score that supports FeasibilityScore.isFeasible().LocalSearchMoveScopes which might win) and picks the winner.HardSoftScores based on the calculation of the hard multiplied by a weight, summed with the soft.String representation of the Score.
ValueSelector implementation.EntitySelector implementation.ValueSelector implementation.MoveSelector.SelectionCacheType.JUST_IN_TIME,
even if a selector child caches.
Score of ScoreHolder.extractScore().
VehicleRoutingSolution's DistanceType.
Score.toLevelNumbers().
SolutionFileIO.getOutputFileExtension(),
because a good output file is able to function as an input file.
Score.toLevelNumbers() for every Score of this definition.
MoveSelectors
s(uch as ChangeMoveSelector and SwapMoveSelector) already handle 1-sized chains.
ProblemFactChanges might be processed:
check BestSolutionChangedEvent.isEveryProblemFactChangeProcessed()
this Solution might be uninitialized: check BestSolutionChangedEvent.isNewBestSolutionInitialized()
this Solution might be infeasible: check FeasibilityScore.isFeasible()
Solution type potentially has its own file extension.
PlannerBenchmarkConfig at runtime before building
the PlannerBenchmark.
DroolsScoreDirector when the Solution needs to be inserted
into an empty KieSession.
Score of this Solution.
Class of the actual Score implementation
Selector with Selector.isNeverEnding() true should return a size
as if it would be able to return each distinct element only once,
because the size can be used in SelectionProbabilityWeightFactory.
IterableSelector.getSize(), but requires an entity.
SolverConfig at runtime before building the Solver.
Solution that is used to calculate the Score.
Score is based on 3 levels of long constraints: hard, medium and soft.Score is based on 3 levels of int constraints: hard, medium and soft.Score is based on 2 levels of BigDecimal constraints: hard and soft.Score is based on 2 levels of double constraints: hard and soft.Score is based on 2 levels of long constraints: hard and soft.Score is based on 2 levels of int constraints: hard and soft.FinalistPodium.RoadSegmentLocation.Score calculation.ScoreDirector, which only recalculates the Score
of the part of the Solution workingSolution that changed,
instead of the going through the entire Solution.ScoreDirectorFactory.ValueSelector applies to) is uninitialized.Scores for a Solution as more and more variables are initialized
(while the already initialized variables don't change).Scores for a Solution as more and more variables are initialized
(while the already initialized variables don't change).PlanningVariable, which implies it's a shadow variable.ScoreDirector.isConstraintMatchEnabled()
for the ScoreDirector which contains this ScoreHolder.
Selector.isNeverEnding() is true.
EntityIndependentValueRangeDescriptor,
otherwise it requires an entity to determine the ValueRange.
ProblemFactChanges have been processed.
Solution is feasible if it has no broken hard constraints.
Solution is feasible if it has no broken hard constraints.
Solution is feasible if it has no broken hard constraints.
PlanningVariable.nullable() value is always considered initialized, but it can still be reinitialized
with PlanningVariable.reinitializeVariableEntityFilter().
Selector.isCountable() is false
or if this selector is in random order (for most cases).
Phase after every step and every move to determine if the search should stop.
Solver after every phase to determine if the search should stop.
Iterable.iterator(), but requires an entity.
Iterable interface that supports ListIterable.listIterator() and ListIterable.listIterator(int).List.listIterator()
List.listIterator()
LocalSearchPhase is a Phase which uses a local search algorithm,
such as tabu search, simulated annealing, ...DefaultPillarSelector.minimumSubPillarSize and DefaultPillarSelector.maximumSubPillarSize,
the sub selection here is a sequence.
DefaultSubChainSelector.minimumSubChainSize and DefaultSubChainSelector.maximumSubChainSize,
the sub selection here is any sub set.
Solution.Iterator of custom Moves.MoveIteratorFactory to a MoveSelector.List of custom Moves.MoveListFactory to a MoveSelector.Moves.ChangeMoveSelectorConfig, etc.DeciderScoreComparatorFactory.Random.nextInt(int) for doubles.
Random.nextInt(int) for longs.
PlanningVariable.nullable().String and returns a Score.
Solver.Forager.pickMove(LocalSearchStepScope).
List of entities that have the same planning value for each (or a subset)
of their planning values.SingleBenchmarkResults of a PlannerBenchmark fail,
the PlannerBenchmark throws this exception
after all SingleBenchmarkResults are finished and the benchmark report has been written.PlannerBenchmark instances.Solver configurations on multiple problem instances (data sets).Solution that implements its own planning cloning
instead of letting the default or a custom SolutionCloner do it.Solution is a collection of planning entities.Solution is a planning entity.Solver configurations.Solution.ProblemBenchmarkResultSingleBenchmarkResultPropertyDescriptor for faster and easier access.NaturalScoreComparator, but is able to compare Scores of different types or nulls.RoadLocation,
but for high scale problems to avoid the memory issue of keeping the entire cost matrix in memory.Scores and what the perfect maximum/minimum Score is.workingSolution
and calculates the Score for that Solution.ScoreDirector.DroolsScoreDirector into the Drools DRL.ValueSelector decorations,
this one works for an entity dependent ValueSelector too.
PlanningEntity, a planningValue, a Move or a Selector).PlanningEntity, a planningValue, a Move or a Selector).List of selection
(which is a PlanningEntity, a planningValue, a Move or a Selector).PlanningEntity, a planningValue, a Move or a Selector).MoveSelector, EntitySelector and ValueSelector
which generates Moves or parts of them.MoveSelectorConfig, EntitySelectorConfig and ValueSelectorConfig.Solver when the Score of this Solution has been calculated.
workingSolution must never be the same instance as the bestSolution,
it should be a (un)changed clone.
Score is based on 1 level of BigDecimal constraints.Score is based on 1 level of double constraints.Score is based on 1 level of long constraints.Score is based on 1 level of int constraints.Solver configuration for 1 problem instance (data set).SingleBenchmarkResultSolution during planning.Object.equals(Object) and Object.hashCode() cannot be used
because the rule engine already requires them (for performance in their original state).
Solution from or to a File.Object.equals(Object) and Object.hashCode() cannot be used
because the rule engine already requires them (for performance in their original state).
Solver configuration benchmarked on multiple problem instances (data sets).Solver instances.BasicPlumbingTermination.waitForRestartSolverDecision()
Solver or a Phase should stop.SolverRankingWeightFactory orders a SolverBenchmarkResult by how how many time each of it's
SingleBenchmarkResult beat the SingleBenchmarkResult of the other SolverBenchmarkResults.Comparator orders a SolverBenchmarkResult by its total Score.CompositeMoveSelector that unions 2 or more MoveSelectors.Selector's Iterator.hasNext() or Iterator.next() methods,
because that can cause descendant Selectors to be selected too early
(which breaks MimicReplayingEntitySelector).FieldAccessingSolutionCloner.isFieldAnEntityPropertyOnSolution(java.lang.reflect.Field) assumptions were wrong.
BendableScore.
BendableBigDecimalScore.
PlanningVariable.ValueRange.PlanningVariable.Comparator orders a SolverBenchmarkResult by its worst Score.Score implementations require specific subclasses:
For BendableScore, use XStreamBendableScoreConverter.Solver with XStream.
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OptaPlanner distribution 6.2.0.Beta2 | |||||||||
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