Modifier and Type | Class and Description |
---|---|
class |
CF_Action |
Modifier and Type | Method and Description |
---|---|
ArrayList<State> |
CF_TransitionProbability.generateFinalStates(State initialState,
Action action) |
ArrayList<State> |
CF_TransitionProbability.getFinalStates(State initialState,
Action action) |
double |
CF_TransitionProbability.getTransitionProbability(State initialState,
Action action,
State finalState) |
Constructor and Description |
---|
CF_ForwardRecursion(umontreal.ssj.probdist.Distribution[] demands,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
ImmediateValueFunction<State,Action,Integer,Double> immediateValueFunctionOutcome,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
CF_ForwardRecursion(umontreal.ssj.probdist.Distribution[] demands,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
ImmediateValueFunction<State,Action,Integer,Double> immediateValueFunctionOutcome,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
CF_ForwardRecursion(umontreal.ssj.probdist.Distribution[] demands,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
ImmediateValueFunction<State,Action,Integer,Double> immediateValueFunctionOutcome,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
CF_ForwardRecursion(umontreal.ssj.probdist.Distribution[] demands,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
ImmediateValueFunction<State,Action,Integer,Double> immediateValueFunctionOutcome,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
CF_ForwardRecursion(umontreal.ssj.probdist.Distribution[] demands,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
ImmediateValueFunction<State,Action,Integer,Double> immediateValueFunctionOutcome,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
CF_ForwardRecursion(umontreal.ssj.probdist.Distribution[] demands,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
ImmediateValueFunction<State,Action,Integer,Double> immediateValueFunctionOutcome,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
CF_StateSpace(int period,
Function<State,ArrayList<Action>> buildActionList,
HashType hashType) |
CF_StateSpace(int period,
Function<State,ArrayList<Action>> buildActionList,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor) |
CF_TransitionProbability(umontreal.ssj.probdist.Distribution[] distributions,
ImmediateValueFunction<State,Action,Integer,Double> immediateValueFunction,
CF_StateSpace[] stateSpace,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
Modifier and Type | Method and Description |
---|---|
Action |
ActionIteratorImpl.next() |
Action |
ActionSampleIteratorImpl.next() |
Modifier and Type | Class and Description |
---|---|
class |
sS_Action |
Modifier and Type | Field and Description |
---|---|
StateTransitionFunction<State,Action,Double> |
sS_TransitionProbability.stateTransitionFunction |
Modifier and Type | Method and Description |
---|---|
Action |
sS_State.getNoAction() |
Modifier and Type | Method and Description |
---|---|
ArrayList<Action> |
sS_State.getFeasibleActions() |
Modifier and Type | Method and Description |
---|---|
ArrayList<State> |
sS_TransitionProbability.generateFinalStates(State initialState,
Action action) |
ArrayList<State> |
sS_TransitionProbability.getFinalStates(State initialState,
Action action) |
double |
sS_TransitionProbability.getTransitionProbability(State initialState,
Action action,
State finalState) |
Modifier and Type | Class and Description |
---|---|
class |
BR_Action |
Modifier and Type | Method and Description |
---|---|
ArrayList<State> |
BR_TransitionProbability.generateFinalStates(State initialState,
Action action) |
ArrayList<State> |
BR_TransitionProbability.getFinalStates(State initialState,
Action action) |
double |
BR_TransitionProbability.getTransitionProbability(State initialState,
Action action,
State finalState) |
Constructor and Description |
---|
BR_ForwardRecursion(int horizonLength,
double[][][] machineLocation,
int[][] fuelConsumption,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType) |
BR_ForwardRecursion(int horizonLength,
double[][][] machineLocation,
int[][] fuelConsumption,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType) |
BR_ForwardRecursion(int horizonLength,
double[][][] machineLocation,
int[][] fuelConsumption,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor) |
BR_ForwardRecursion(int horizonLength,
double[][][] machineLocation,
int[][] fuelConsumption,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor) |
BR_StateSpace(int period,
Function<State,ArrayList<Action>> buildActionList,
HashType hashType) |
BR_StateSpace(int period,
Function<State,ArrayList<Action>> buildActionList,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor) |
Modifier and Type | Class and Description |
---|---|
class |
BRF_Action |
Modifier and Type | Method and Description |
---|---|
ArrayList<State> |
BRF_TransitionProbability.generateFinalStates(State initialState,
Action action) |
ArrayList<State> |
BRF_TransitionProbability.getFinalStates(State initialState,
Action action) |
double |
BRF_TransitionProbability.getTransitionProbability(State initialState,
Action action,
State finalState) |
Constructor and Description |
---|
BRF_ForwardRecursion(int horizonLength,
double[][][] machineLocation,
umontreal.ssj.probdist.DiscreteDistribution[][] fuelConsumption,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
BRF_ForwardRecursion(int horizonLength,
double[][][] machineLocation,
umontreal.ssj.probdist.DiscreteDistribution[][] fuelConsumption,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
BRF_StateSpace(int period,
Function<State,ArrayList<Action>> buildActionList,
HashType hashType) |
BRF_StateSpace(int period,
Function<State,ArrayList<Action>> buildActionList,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor) |
Modifier and Type | Class and Description |
---|---|
class |
BRL_Action |
Modifier and Type | Method and Description |
---|---|
ArrayList<State> |
BRL_TransitionProbability.generateFinalStates(State initialState,
Action action) |
ArrayList<State> |
BRL_TransitionProbability.getFinalStates(State initialState,
Action action) |
double |
BRL_TransitionProbability.getTransitionProbability(State initialState,
Action action,
State finalState) |
Constructor and Description |
---|
BRL_ForwardRecursion(int horizonLength,
double[][][] machineLocation,
int[][] fuelConsumption,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
BRL_ForwardRecursion(int horizonLength,
double[][][] machineLocation,
int[][] fuelConsumption,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
Function<State,ArrayList<Action>> buildActionList,
double discountFactor,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor,
SamplingScheme samplingScheme,
int sampleSize,
double reductionFactorPerStage) |
BRL_StateSpace(int period,
Function<State,ArrayList<Action>> buildActionList,
HashType hashType) |
BRL_StateSpace(int period,
Function<State,ArrayList<Action>> buildActionList,
HashType hashType,
int stateSpaceSizeLowerBound,
float loadFactor) |
Modifier and Type | Field and Description |
---|---|
protected static Function<State,ArrayList<Action>> |
StateSpace.buildActionList |
protected static Function<State,Action> |
StateSpace.idempotentAction |
protected ImmediateValueFunction<State,Action,Double> |
ValueRepository.immediateValueFunction |
protected Map<State,Action> |
ValueRepository.optimalActionHashTable |
Modifier and Type | Method and Description |
---|---|
Action |
BestActionRepository.getBestAction()
Returns the best action stored.
|
Action |
State.getNoAction()
Returns the idempotent
Action for this State . |
Action |
ValueRepository.getOptimalAction(State state)
Returns the optimal action associated with
state . |
abstract Action |
ActionIterator.next() |
Modifier and Type | Method and Description |
---|---|
static Function<State,ArrayList<Action>> |
StateSpace.getBuildActionList() |
ArrayList<Action> |
State.getFeasibleActions()
Returns an
ArrayList<Action> of feasible actions for this
State . |
static Function<State,Action> |
StateSpace.getIdempotentAction() |
Map<State,Action> |
ValueRepository.getOptimalActionHashTable()
Returns the hashtable storing optimal actions.
|
Modifier and Type | Method and Description |
---|---|
abstract ArrayList<State> |
TransitionProbability.generateFinalStates(State initialState,
Action action)
This method constructs an
ArrayList<State> of states towards which the stochastic process may
transition in period t+1 if action is selected in initialState at period
t ; note that these states may not yet exist in the state space. |
double |
ValueRepository.getExpectedValue(State initialState,
Action action,
TransitionProbability transitionProbability)
Returns the expected value associated with
initialState and action under one-step transition probabilities
described in transitionProbability . |
abstract ArrayList<State> |
TransitionProbability.getFinalStates(State initialState,
Action action)
This method retrieves an
ArrayList<State> of existing states towards which the stochastic process may
transition in period t+1 if action is selected in initialState at period
t . |
double |
ValueRepository.getImmediateValue(State initialState,
Action action,
State finalState)
Returns the immediate value of a transition from
initialState to finalState under a chosen action . |
abstract double |
TransitionProbability.getTransitionProbability(State initialState,
Action action,
State finalState)
This method returns the transition probability from
initialState to finalState when
action is selected. |
void |
ValueRepository.setOptimalAction(State state,
Action action)
Associates an optimal action
action to state state . |
void |
BestActionRepository.update(Action currentAction,
double currentValue)
Compares
currentAction and currentValue to the best action currently stored and updates
values stored accordingly. |
Modifier and Type | Method and Description |
---|---|
void |
ValueRepository.setImmediateValue(ImmediateValueFunction<State,Action,Double> immediateValueFunction)
Sets the immediate value function of a transition from
initialState to finalState under a chosen action . |
Constructor and Description |
---|
StateAction(State initialState,
Action action)
Creates an instance of
StateAction from state initialState and action action . |
Constructor and Description |
---|
ValueRepository(ImmediateValueFunction<State,Action,Double> immediateValueFunction,
double discountFactor,
HashType hash)
Creates a new value repository.
|
ValueRepository(ImmediateValueFunction<State,Action,Double> immediateValueFunction,
double discountFactor,
int stateSpaceSizeLowerBound,
float loadFactor,
HashType hash)
Creates a new value repository.
|
Modifier and Type | Class and Description |
---|---|
class |
ActionImpl
A concrete implementation of
Action . |
Modifier and Type | Field and Description |
---|---|
protected RandomOutcomeFunction<State,Action,double[]> |
TransitionProbabilityImpl.randomOutcomeFunction |
Modifier and Type | Method and Description |
---|---|
ArrayList<State> |
TransitionProbabilityImpl.generateFinalStates(State initialState,
Action action) |
ArrayList<State> |
TransitionProbabilityImpl.getFinalStates(State initialState,
Action action) |
double |
TransitionProbabilityImpl.getTransitionProbability(State initialState,
Action action,
State finalState) |
Constructor and Description |
---|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdistmulti.DiscreteDistributionIntMulti[] demand,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initialises state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdistmulti.DiscreteDistributionIntMulti[] demand,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initialises state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdistmulti.DiscreteDistributionIntMulti[] demand,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initialises state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdistmulti.DiscreteDistributionIntMulti[] demand,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initialises state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdistmulti.DiscreteDistributionIntMulti[] demand,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor,
HashType hash)
Creates an instance of the problem and initialises state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdistmulti.DiscreteDistributionIntMulti[] demand,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor,
HashType hash)
Creates an instance of the problem and initialises state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdistmulti.DiscreteDistributionIntMulti[] demand,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor,
HashType hash)
Creates an instance of the problem and initialises state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdistmulti.DiscreteDistributionIntMulti[] demand,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor,
HashType hash)
Creates an instance of the problem and initialises state space, transition probability and value repository.
|
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash,
int stateSpaceSizeLowerBound,
float loadFactor) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash,
int stateSpaceSizeLowerBound,
float loadFactor) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash,
int stateSpaceSizeLowerBound,
float loadFactor) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash,
int stateSpaceSizeLowerBound,
float loadFactor) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
SamplingScheme samplingScheme,
int maxSampleSize,
HashType hash,
double reductionFactorPerStage) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
SamplingScheme samplingScheme,
int maxSampleSize,
HashType hash,
double reductionFactorPerStage) |
TransitionProbabilityImpl(umontreal.ssj.probdistmulti.DiscreteDistributionIntMulti[] multiVariateDistributions,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
StateSpaceImpl[] stateSpace) |
TransitionProbabilityImpl(MultiINIDistribution[] multiVariateDistributions,
RandomOutcomeFunction<State,Action,double[]> randomOutcomeFunction,
StateSpaceImpl[] stateSpace) |
Modifier and Type | Field and Description |
---|---|
protected RandomOutcomeFunction<State,Action,Double> |
TransitionProbabilityImpl.randomOutcomeFunction |
Modifier and Type | Method and Description |
---|---|
ArrayList<State> |
TransitionProbabilityImpl.generateFinalStates(State initialState,
Action action) |
ArrayList<State> |
TransitionProbabilityImpl.getFinalStates(State initialState,
Action action) |
double |
TransitionProbabilityImpl.getTransitionProbability(State initialState,
Action action,
State finalState) |
Constructor and Description |
---|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[][][] demand,
double[][][] supportLB,
double[][][] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[][][] demand,
double[][][] supportLB,
double[][][] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[][][] demand,
double[][][] supportLB,
double[][][] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[][][] demand,
double[][][] supportLB,
double[][][] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[][] demand,
double[][] supportLB,
double[][] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[][] demand,
double[][] supportLB,
double[][] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[][] demand,
double[][] supportLB,
double[][] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[][] demand,
double[][] supportLB,
double[][] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[] demand,
double[] supportLB,
double[] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[] demand,
double[] supportLB,
double[] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[] demand,
double[] supportLB,
double[] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[] demand,
double[] supportLB,
double[] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[] demand,
double[] supportLB,
double[] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[] demand,
double[] supportLB,
double[] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[] demand,
double[] supportLB,
double[] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
BackwardRecursionImpl(Recursion.OptimisationDirection optimisationDirection,
umontreal.ssj.probdist.Distribution[] demand,
double[] supportLB,
double[] supportUB,
ImmediateValueFunction<State,Action,Double> immediateValueFunction,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
double discountFactor,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor,
HashType hash)
Creates an instance of the problem and initializes state space, transition probability and value repository.
|
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash,
int stateSpaceSizeLowerBound,
float loadFactor) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash,
int stateSpaceSizeLowerBound,
float loadFactor) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor) |
StateSpaceImpl(int period,
Function<State,ArrayList<Action>> buildActionList,
Function<State,Action> idempotentAction,
HashType hash,
SamplingScheme samplingScheme,
int maxSampleSize,
double reductionFactorPerStage,
int stateSpaceSizeLowerBound,
float loadFactor) |
TransitionProbabilityImpl(umontreal.ssj.probdist.Distribution[][][] distributions,
double[][][] supportLB,
double[][][] supportUB,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
StateSpaceImpl[] stateSpace,
double stepSize) |
TransitionProbabilityImpl(umontreal.ssj.probdist.Distribution[] distributions,
double[] supportLB,
double[] supportUB,
RandomOutcomeFunction<State,Action,Double> randomOutcomeFunction,
StateSpaceImpl[] stateSpace,
double stepSize) |
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