Piecewise constant and piecewise linear decision rule approximator. More...

#include <PWDecisionRule.hpp>

Inheritance diagram for PiecewiseDecisionRule:

Collaboration diagram for PiecewiseDecisionRule:

Public Member Functions
	PiecewiseDecisionRule (const map< string, uint > &numPartitionsMap=map< string, uint >(), double bigM=100., bool useExplicitNACs=false, string folder=" ")
	Constructor of the PiecewiseDecisionRule class. More...

	~PiecewiseDecisionRule ()
	Constructor of the PiecewiseApproximator class Directly initialize with the predefined private members (for greater customization) More...

ROCPPOptModelIF_Ptr	approximate (ROCPPOptModelIF_Ptr pIn)
	Approximate the input model First construct the partition maps, then calculate and robustity the model on each subset, finally add non-anticipativity constraints. More...

string	getSolutionApproachParameters (string delimiter) const
	Return a new model after fixing the binary variables to the value provided in the input map. More...

pair< bool, ROCPPVarIF_Ptr >	findOrigVariable (ROCPPVarIF_Ptr newdv) const
	Find the variable that new decision variable originated from after LDR and CDR. More...

ROCPPVarIF_Ptr	getVarOnPartition (string partition, string origVarName) const
	Get the decision variable on the the given subset of the partition for the given original variable. More...

void	calculateSolution (ROCPPOptModelIF_Ptr pIn, const map< string, double > &resultIn, ROCPPVarIF_Ptr dv, string partition)
	Calculate solution for the given variable on the given subset of the partition. More...

void	calculateSolution (ROCPPOptModelIF_Ptr pIn, const map< string, double > &resultIn, ROCPPUnc_Ptr unc, string partition)
	Calculate the measurement variable value for the given uncertainty on the given subset of the partition. More...

void	getWsSolutions (ROCPPOptModelIF_Ptr pIn, const map< string, double > &warmStartResults, const map< string, uint > &wsMap, map< string, double > &wsSolutions)
	Return the warm start solution of this problem by setting the variables which exist in the warm start problem to their solutions and assigning the variables which do not exist in the warm start problem to the solutions on the nearest partition. More...

void	printParametersToScreen () const

void	printOut (const ROCPPOptModelIF_Ptr pIn, const map< string, double > &resultIn, ROCPPVarIF_Ptr dv, map< ROCPPUnc_Ptr, uint > partitionIn)
	Print out the solution for the given variable on the given subset of the partition. More...

void	printOut (const ROCPPOptModelIF_Ptr pIn, const map< string, double > &resultIn, ROCPPVarIF_Ptr dv)
	Print out the solution for the given variable on all subsets of the the partition. More...

void	printOut (const ROCPPOptModelIF_Ptr pIn, const map< string, double > &resultIn, ROCPPUnc_Ptr unc, map< ROCPPUnc_Ptr, uint > partitionIn)
	Print out whether observe or not the given uncertainty on the given subset of the partition. More...

void	printOut (const ROCPPOptModelIF_Ptr pIn, const map< string, double > &resultIn, ROCPPUnc_Ptr unc)
	Print out whether we observe or not the given uncertainty on all subsets of the partition. More...

ROCPPOptModelIF_Ptr	Reformulate (ROCPPOptModelIF_Ptr pIn)

bool	isApplicable (ROCPPOptModelIF_Ptr pIn) const

string	getName () const

Public Member Functions inherited from DecisionRuleIF
	DecisionRuleIF (uint memory=1000)
	Constructor of the DecisionRuleIF class. More...

virtual	~DecisionRuleIF ()
	Destructor of the DecisionRuleIF class. More...

uint	getMemory () const

Public Member Functions inherited from ReformulationStrategyIF
	ReformulationStrategyIF ()

	~ReformulationStrategyIF ()

Private Member Functions
void	initialize (ROCPPOptModelIF_Ptr pIn)
	Initialize the class with the given parameters. More...

void	createVariableMap (ROCPPOptModelIF_Ptr pIn, ROCPPOptModelIF_Ptr pMiddle, vector< ROCPPConstraintIF_Ptr > &vecNACs)
	Create the map from partition to map from variable in original problem to variable on partition. More...

void	createUncertaintyMap (ROCPPOptModelIF_Ptr pIn)
	Create the map from partition to map from uncertain parameter in original problem to uncertainty on partition. More...

pair< double, map< string, ROCPPExpr_Ptr > >	calculateMeanAndProb (ROCPPOptModelIF_Ptr pModel, string partition, const map< string, pair< double, double > > &allMap, double allArea)
	Calculate the probability of the given subset of the partition and the means of the uncertain parameters on it. More...

ROCPPExpr_Ptr	getStochasticObj (const pair< double, map< string, ROCPPExpr_Ptr > > &meanAndProb, const ROCPPObjectiveIF_Ptr oldObj, string partitionSubsetNme)
	Calculate the value of the objective on the given subset of the partition. More...

Private Attributes
string	m_numPartitionsStr
	String encoding the number of subsets in the partition for every observable uncertainty in the problem, in alphabetical order. More...

ROCPPContinuousVarsDR_Ptr	m_pCVA
	Linear decision rule converter. More...

ROCPPDiscreteVarsDR_Ptr	m_pDVA
	Constant decision rule converter. More...

ROCPPMItoMB_Ptr	m_pMItoMB_Bilinear

ROCPPUncSetRealVarApprox_Ptr	m_pBPA

ROCPPParConstructor_Ptr	m_pPartConstructor
	Partition constructor of this approximator. More...

ROCPPParConverter_Ptr	m_pPartConverter
	Partition converter of this approximator. More...

map< string, map< string, ROCPPVarIF_Ptr > >	m_VariableMap
	Map from subset of partition to map from variable in original problem to variable on subset of the partition. More...

bool	m_useExplicitNACs
	Use constraints to describe the non anticipativity constraints. More...

double	m_bigM
	Value of the big M constant. More...

map< string, uint >	m_numPartitionsMap

string	m_folder
	Name of the folder where to write the text file. More...

uint	m_numBits
	Number of bits used to approximate the real valued variables affecting the uncertainty set. More...

Additional Inherited Members
Protected Attributes inherited from DecisionRuleIF
uint	m_memory
	Memory of this approximator. More...

Detailed Description

Piecewise constant and piecewise linear decision rule approximator.

Warning: : only applies to problems where the uncertainty set only depends on binary variables

Constructor & Destructor Documentation

◆ PiecewiseDecisionRule()

PiecewiseDecisionRule::PiecewiseDecisionRule	(	const map< string, uint > &	numPartitionsMap = `map<string, uint>()`,
		double	bigM = `100.`,
		bool	useExplicitNACs = `false`,
		string	folder = `" "`
	)

Constructor of the PiecewiseDecisionRule class.

Parameters

numPartitionsMap	map from the name of the uncertain parameter to the number of subsets along that direction (number of breakpoints + 1)
bigM	Big-M value used for linearizing the bilinear terms
useExplicitNACs	If true, then two meansurement variables are equal, otherwise use the same measurement variables for the NACs
folder	Name of folders where to store the log file

◆ ~PiecewiseDecisionRule()

PiecewiseDecisionRule::~PiecewiseDecisionRule ( )

inline

Constructor of the PiecewiseApproximator class Directly initialize with the predefined private members (for greater customization)

Destructor of the PiecewiseApproximator class

Member Function Documentation

◆ approximate()

ROCPPOptModelIF_Ptr PiecewiseDecisionRule::approximate ( ROCPPOptModelIF_Ptr pIn )

virtual

Approximate the input model First construct the partition maps, then calculate and robustity the model on each subset, finally add non-anticipativity constraints.

Implements DecisionRuleIF.

◆ calculateMeanAndProb()

pair< double, map< string, ROCPPExpr_Ptr > > PiecewiseDecisionRule::calculateMeanAndProb	(	ROCPPOptModelIF_Ptr	pModel,
		string	partition,
		const map< string, pair< double, double > > &	allMap,
		double	allArea
	)

private

Calculate the probability of the given subset of the partition and the means of the uncertain parameters on it.

◆ calculateSolution() [1/2]

void PiecewiseDecisionRule::calculateSolution	(	ROCPPOptModelIF_Ptr	pIn,
		const map< string, double > &	resultIn,
		ROCPPUnc_Ptr	unc,
		string	partition
	)

Calculate the measurement variable value for the given uncertainty on the given subset of the partition.

◆ calculateSolution() [2/2]

void PiecewiseDecisionRule::calculateSolution	(	ROCPPOptModelIF_Ptr	pIn,
		const map< string, double > &	resultIn,
		ROCPPVarIF_Ptr	dv,
		string	partition
	)

Calculate solution for the given variable on the given subset of the partition.

◆ createUncertaintyMap()

void PiecewiseDecisionRule::createUncertaintyMap ( ROCPPOptModelIF_Ptr pIn )

private

Create the map from partition to map from uncertain parameter in original problem to uncertainty on partition.

◆ createVariableMap()

void PiecewiseDecisionRule::createVariableMap	(	ROCPPOptModelIF_Ptr	pIn,
		ROCPPOptModelIF_Ptr	pMiddle,
		vector< ROCPPConstraintIF_Ptr > &	vecNACs
	)

private

Create the map from partition to map from variable in original problem to variable on partition.

◆ findOrigVariable()

pair< bool, ROCPPVarIF_Ptr > PiecewiseDecisionRule::findOrigVariable ( ROCPPVarIF_Ptr newdv ) const

Find the variable that new decision variable originated from after LDR and CDR.

◆ getName()

string PiecewiseDecisionRule::getName ( ) const

inlinevirtual

Implements ReformulationStrategyIF.

◆ getSolutionApproachParameters()

string PiecewiseDecisionRule::getSolutionApproachParameters ( string delimiter ) const

Return a new model after fixing the binary variables to the value provided in the input map.

◆ getStochasticObj()

ROCPPExpr_Ptr PiecewiseDecisionRule::getStochasticObj	(	const pair< double, map< string, ROCPPExpr_Ptr > > &	meanAndProb,
		const ROCPPObjectiveIF_Ptr	oldObj,
		string	partitionSubsetNme
	)

private

Calculate the value of the objective on the given subset of the partition.

◆ getVarOnPartition()

ROCPPVarIF_Ptr PiecewiseDecisionRule::getVarOnPartition	(	string	partition,
		string	origVarName
	)		const

Get the decision variable on the the given subset of the partition for the given original variable.

◆ getWsSolutions()

void PiecewiseDecisionRule::getWsSolutions	(	ROCPPOptModelIF_Ptr	pIn,
		const map< string, double > &	warmStartResults,
		const map< string, uint > &	wsMap,
		map< string, double > &	wsSolutions
	)

Return the warm start solution of this problem by setting the variables which exist in the warm start problem to their solutions and assigning the variables which do not exist in the warm start problem to the solutions on the nearest partition.

Parameters

pIn	Model before approximating
warmStartResults	Results of the warm start problem
wsMap	Map from time stage to number of k in the warm start problem
wsSolutions	Map from variable name to its warm start solution for all variables in the problem to be solved

◆ initialize()

void PiecewiseDecisionRule::initialize ( ROCPPOptModelIF_Ptr pIn )

private

Initialize the class with the given parameters.

◆ isApplicable()

bool PiecewiseDecisionRule::isApplicable ( ROCPPOptModelIF_Ptr pIn ) const

virtual

Implements ReformulationStrategyIF.

◆ printOut() [1/4]

void PiecewiseDecisionRule::printOut	(	const ROCPPOptModelIF_Ptr	pIn,
		const map< string, double > &	resultIn,
		ROCPPUnc_Ptr	unc
	)

Print out whether we observe or not the given uncertainty on all subsets of the partition.

◆ printOut() [2/4]

void PiecewiseDecisionRule::printOut	(	const ROCPPOptModelIF_Ptr	pIn,
		const map< string, double > &	resultIn,
		ROCPPUnc_Ptr	unc,
		map< ROCPPUnc_Ptr, uint >	partitionIn
	)

Print out whether observe or not the given uncertainty on the given subset of the partition.

◆ printOut() [3/4]

void PiecewiseDecisionRule::printOut	(	const ROCPPOptModelIF_Ptr	pIn,
		const map< string, double > &	resultIn,
		ROCPPVarIF_Ptr	dv
	)

Print out the solution for the given variable on all subsets of the the partition.

◆ printOut() [4/4]

void PiecewiseDecisionRule::printOut	(	const ROCPPOptModelIF_Ptr	pIn,
		const map< string, double > &	resultIn,
		ROCPPVarIF_Ptr	dv,
		map< ROCPPUnc_Ptr, uint >	partitionIn
	)

Print out the solution for the given variable on the given subset of the partition.

◆ printParametersToScreen()

void PiecewiseDecisionRule::printParametersToScreen ( ) const

◆ Reformulate()

ROCPPOptModelIF_Ptr PiecewiseDecisionRule::Reformulate ( ROCPPOptModelIF_Ptr pIn )

inlinevirtual

Implements ReformulationStrategyIF.

Member Data Documentation

◆ m_bigM

double PiecewiseDecisionRule::m_bigM

private

Value of the big M constant.

◆ m_folder

string PiecewiseDecisionRule::m_folder

private

Name of the folder where to write the text file.

◆ m_numBits

uint PiecewiseDecisionRule::m_numBits

private

Number of bits used to approximate the real valued variables affecting the uncertainty set.

◆ m_numPartitionsMap

map<string,uint> PiecewiseDecisionRule::m_numPartitionsMap

private

◆ m_numPartitionsStr

string PiecewiseDecisionRule::m_numPartitionsStr

private

String encoding the number of subsets in the partition for every observable uncertainty in the problem, in alphabetical order.

◆ m_pBPA

ROCPPUncSetRealVarApprox_Ptr PiecewiseDecisionRule::m_pBPA

private

◆ m_pCVA

ROCPPContinuousVarsDR_Ptr PiecewiseDecisionRule::m_pCVA

private

Linear decision rule converter.

◆ m_pDVA

ROCPPDiscreteVarsDR_Ptr PiecewiseDecisionRule::m_pDVA

private

Constant decision rule converter.

◆ m_pMItoMB_Bilinear

ROCPPMItoMB_Ptr PiecewiseDecisionRule::m_pMItoMB_Bilinear

private

◆ m_pPartConstructor

ROCPPParConstructor_Ptr PiecewiseDecisionRule::m_pPartConstructor

private

Partition constructor of this approximator.

◆ m_pPartConverter

ROCPPParConverter_Ptr PiecewiseDecisionRule::m_pPartConverter

private

Partition converter of this approximator.

◆ m_useExplicitNACs

bool PiecewiseDecisionRule::m_useExplicitNACs

private

Use constraints to describe the non anticipativity constraints.

◆ m_VariableMap

map<string, map<string,ROCPPVarIF_Ptr> > PiecewiseDecisionRule::m_VariableMap

private

Map from subset of partition to map from variable in original problem to variable on subset of the partition.

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ PiecewiseDecisionRule()

◆ ~PiecewiseDecisionRule()

Member Function Documentation

◆ approximate()

◆ calculateMeanAndProb()

◆ calculateSolution() [1/2]

◆ calculateSolution() [2/2]

◆ createUncertaintyMap()

◆ createVariableMap()

◆ findOrigVariable()

◆ getName()

◆ getSolutionApproachParameters()

◆ getStochasticObj()

◆ getVarOnPartition()

◆ getWsSolutions()

◆ initialize()

◆ isApplicable()

◆ printOut() [1/4]

◆ printOut() [2/4]

◆ printOut() [3/4]

◆ printOut() [4/4]

◆ printParametersToScreen()

◆ Reformulate()

Member Data Documentation

◆ m_bigM

◆ m_folder

◆ m_numBits

◆ m_numPartitionsMap

◆ m_numPartitionsStr

◆ m_pBPA

◆ m_pCVA

◆ m_pDVA

◆ m_pMItoMB_Bilinear

◆ m_pPartConstructor

◆ m_pPartConverter

◆ m_useExplicitNACs

◆ m_VariableMap