ApproximationControl
Controls for functions related to state space approximation
IsApplyStateFiltering
public override bool IsApplyStateFiltering()Definition
Defines whether to filter the state to be explored. There are two types of logic for filtering states:
Global filtering: filters on states in stages.
Local filtering: filters on state transitions.
Return
Boolean
Whether to apply state filtering logic.
False
Example (Default Logic)
public override bool IsApplyStateFiltering()
{
return false;
}IsApplyApproximation
public override bool IsApplyApproximation()Definition
Whether to apply the approximation method to filter the states during global filtering.
Return
Boolean
Whether to apply approximation logic to global filtering.
False
Example (Default Logic)
public override bool IsApplyApproximation()
{
return false;
}IsUseEstimationValue
public override bool IsUseEstimationValue()Definition
Set whether to calculate and utilize value estimates in states.
Return
Boolean
True: Apply False: Do not apply
False
Example (Default Logic)
public override bool IsUseEstimationValue()
{
return false;
}GetEstimationValueUpdatePeriod
public override int GetEstimationValueUpdatePeriod()Definition
Sets the frequency at which the value estimate is calculated for a state. In other words, if that frequency is n, then every nth state, the value estimate for the state is calculated.
Return
Integer
The frequency at which the value estimate of the state is calculated.
1
Example (Default Logic)
public override int GetEstimationValueUpdatePeriod()
{
return 1;
}GetEstimationValueStopStageIndex
public override int GetEstimationValueStopStageIndex()Definition
Set the stage index at which to stop calculating the estimated value of the state. In other words, if the value is n and the stage Index is greater than n, the state value estimate is not calculated.
Return
Integer
The stage index at which to start calculating the estimated value of the state.
Int32.MaxValue
Example (Default Logic)
public override int GetEstimationValueStopStageIndex()
{
return Int32.MaxValue;
}GetStateFilteringType
public override StateFilteringType GetStateFilteringType()Definition
Set up logic to filter the states to explore.
Return
Example (Default Logic)
public override StateFilteringType GetStateFilteringType()
{
return StateFilteringType.Global;
}GetGlobalTransitionCount
public override int GetGlobalTransitionCount()Definition
Sets the number of states to explore when applying global filtering. For example, if you set the value to 1000, only 1000 states will remain in the stage, and the remaining states will be excluded.
Definition
Integer
The number of states to explore after global filtering.
1000
Example (Default Logic)
public override int GetGlobalTransitionCount()
{
return 1000;
}GetApproximationTransitionCount
public override int GetApproximationTransitionCount() Definition
Sets the number of states to explore when applying global filtering using the approximation method. For example, if you set the value to 1000, only 1000 states will remain in the stage, and the remaining states will be excluded.
Return
Integer
The number of states to explore after global filtering using the approximation method.
10
Example (Default Logic)
public override int GetApproximationTransitionCount()
{
return 10;
}GetClusterTransitionCount
public override int GetClusterTransitionCount()Definition
Sets the number of states to explore when applying global filtering using the state clustering method. For example, if you set the value to 10, only 10 states will remain in the stage, and the remaining states will be excluded.
Return
Integer
The number of states to explore after global filtering using the state clustering method.
2
Example (Default Logic)
public override int GetClusterTransitionCount()
{
return 2;
}GetLocalTransitionCount
public override int GetLocalTransitionCount()Definition
Sets the number of states to explore when applying local filtering. For example, if you set the value to 1, only 1 of the state transitions from a state will be selected to navigate to the next state defined in that transition.
Return
Integer
The number of states to explore after local filtering.
1
Example (Default Logic)
public override int GetLocalTransitionCount()
{
return 1;
}GetGlobalFilteringStartStageIndex
public override int GetGlobalFilteringStartStageIndex()Definition
Sets the stage index to start applying the global filtering logic. For example, if you set this value to 0, the global filtering logic will be applied to all stages with an Index greater than or equal to 0.
Return
Integer
The stage index to start applying the global filtering logic.
0
Example (Default Logic)
public override int GetGlobalFilteringStartStageIndex()
{
return 0;
}GetLocalFilteringStartStageIndex
public override int GetLocalFilteringStartStageIndex()Definition
Sets the stage index to start applying the local filtering logic. For example, if you set this value to 0, the local filtering logic will be applied to all stages with an Index greater than or equal to 0.
Return
Integer
The stage index to start applying the local filtering logic.
0
Example (Default Logic)
public override int GetLocalFilteringStartStageIndex()
{
return 0;
}GetApproximationStartStageIndex
public override int GetApproximationStartStageIndex()Definition
Sets the stage index to start applying the global filtering logic using approximation method. For example, if you set this value to 0, the approximation method will be applied to all stages with an Index greater than or equal to 0.
Return
Integer
The stage index to start applying the global filtering logic using approximation method.
0
Example (Default Logic)
public override int GetApproximationStartStageIndex()
{
return 0;
}GetMinimumTransitionCost
public override double GetMinimumTransitionCost()Definition
Sets the smallest transition cost for all possible transitions. This value is a parameter used to filter the states to be explored by the approximation method.
Return
Integer
The smallest possible transition cost.
0
Example (Default Logic)
public override double GetMinimumTransitionCost()
{
return 0;
}GetMultiplier
public override double GetMultiplier()Definition
This parameter is used to filter the states to be explored by the approximation method. The higher the value, the more states will be explored, increasing computation time and potentially improving the objective function value.
Return
Double
The value of the multiplier parameter.
2
Example (Default Logic)
public override double GetMultiplier()
{
return 2;
}GetEstimatedValue
public override double GetEstimatedValue(State state)Definition
Sets an estimate of the value function of a given state. This estimate is used to apply approximation method to reduce the number of states to explore.
Parameters
State
The state to compute the value function estimate.
Return
Example (Default Logic)
public override double GetEstimatedValue(State state)
{
double dualBound = BoundControl.Instance.GetDualBound(state);
state.SetDualBound(dualBound);
return state.BestValue + state.DualBound;
}FilterGlobalStates
public override List<State> FilterGlobalStates(List<State> states, int maxTransitionCount, ObjectiveFunctionType objectiveFunctionType, double pruneTolerance, bool isApplyStateClustering)Definition
Defines the global filtering logic and returns a list of states to explore.
Parameters
List<State>
The list of states before filtering.
Integer
The maximum number of states to explore after filtering.
ObjectiveFunctionType
The type of objective function in the problem. (Maximize, Minimize)
Double
The tolerance value that is applied when determining the state pruning condition.
Boolean
Whether to apply state clustering method.
Return
Example (Default Logic)
public override List<State> FilterGlobalStates(List<State> states, int maxTransitionCount, ObjectiveFunctionType objectiveFunctionType, double pruneTolerance, bool isApplyStateClustering)
{
List<State> filtered = new List<State>();
if (isApplyStateClustering)
{
Dictionary<int, List<State>> clusters = new Dictionary<int, List<State>>();
foreach (State state in states)
{
if (clusters.TryGetValue(state.ClusterID, out List<State> list) == false)
{
clusters.Add(state.ClusterID, new List<State>() { state });
}
else
{
list.Add(state);
}
}
int clusterTransitionCount = this.GetClusterTransitionCount();
foreach (KeyValuePair<int, List<State>> item in clusters)
{
List<State> list = item.Value.OrderBy(x => x.ClusterDistance).ToList();
int maxCount = clusterTransitionCount;
int count = 0;
foreach (State st in list)
{
if (count > maxCount)
break;
filtered.Add(st);
count++;
}
}
}
else
{
foreach (State state in states)
{
if (state.IsFinal)
continue;
double estimatedValue = GetEstimatedValue(state);
state.EstimationValue = estimatedValue;
}
if (objectiveFunctionType == ObjectiveFunctionType.Minimize)
states = states.OrderBy(x => x.EstimationValue).ToList();
else if (objectiveFunctionType == ObjectiveFunctionType.Maximize)
states = states.OrderByDescending(x => x.EstimationValue).ToList();
int count = 0;
foreach (State state in states)
{
if (maxTransitionCount <= count)
break;
filtered.Add(state);
count++;
}
}
return filtered;
}FilterLocalStates
public override List<State> FilterLocalStates(List<State> states, int maxTransitionCount)Definition
Defines the local filtering logic and returns a list of states to explore.
Parameters
List<State>
The list of states before filtering.
Integer
The maximum number of states to explore after filtering.
Return
Example (Default Logic)
public override List<State> FilterLocalStates(List<State> states, int maxTransitionCount)
{
states = states.OrderBy(x => x.PrevBestState.DualBound + (x.BestValue - x.PrevBestState.BestValue) + x.BestValue).ToList();
List<State> filtered = new List<State>();
int count = 0;
foreach (State state in states)
{
if (maxTransitionCount <= count)
break;
filtered.Add(state);
count++;
}
return filtered;
}CanPruneByApproximation
public override bool CanPruneByApproximation(State state, ObjectiveFunctionType objFuncType, double minEstimationValue, double minTransitionCost, double multiplier, double pruneTolerance)Definition
Sets whether a given state should be excluded from exploration when reducing the number of states to explore via approximation methods.
Parameters
State
The state to be evaluated.
ObjectiveFunctionType
The type of objective function in the problem. (Maximize, Minimize)
Double
The smallest of the value function estimates of the candidate states to explore.
Double
The smallest possible transition cost.
Double
The value of the multiplier parameter.
Double
The tolerance value that is applied when determining the state pruning condition.
Return
Example (Default Logic)
public override bool CanPruneByApproximation(State state, ObjectiveFunctionType objFuncType, double minEstimationValue, double minTransitionCost, double multiplier, double pruneTolerance)
{
if (state.IsFinal)
return false;
if (objFuncType == ObjectiveFunctionType.Minimize)
{
if (state.EstimationValue + pruneTolerance > minEstimationValue + (minTransitionCost * multiplier))
return true;
else
return false;
}
else
{
if (state.EstimationValue + pruneTolerance < minEstimationValue + (minTransitionCost * multiplier))
return true;
else
return false;
}
}Last updated