choco.real.search
Class AbstractRealOptimize

java.lang.Object
  choco.AbstractEntity
      choco.AbstractSolver
          choco.search.AbstractGlobalSearchSolver
              choco.real.search.AbstractRealOptimize

All Implemented Interfaces:

Entity

Direct Known Subclasses:

RealBranchAndBound, RealOptimizeWithRestarts

public abstract class AbstractRealOptimize
extends AbstractGlobalSearchSolver

J-CHOCO Copyright (C) F. Laburthe, 1999-2003

An open-source Constraint Programming Kernel for Research and Education

Created by: Guillaume on 20 juil. 2004

Field Summary

boolean	doMaximize a boolean indicating whether we want to maximize (true) or minize (false) the objective variable
double	lowerBound the lower bound of the objective value.
RealVar	objective the variable modelling the objective value
double	targetLowerBound a tentative lower bound
double	targetUpperBound a tentative upper bound
double	upperBound the upper bound of the objective value This value comes from the problem definition; it is strengthened by the search history (solutions found & no-goods)

Fields inherited from class choco.search.AbstractGlobalSearchSolver

baseWorld, currentTraceIndex, DOWN_BRANCH, encounteredLimit, INIT_SEARCH, limits, loggingMaxDepth, mainGoal, nbSolutions, nextMove, OPEN_NODE, stopAtFirstSol, traceStack, UP_BRANCH

Fields inherited from class choco.AbstractSolver

logger, maxNbSolutionStored, solutions

Fields inherited from class choco.AbstractEntity

hook, problem

Constructor Summary

protected

AbstractRealOptimize(RealVar obj, boolean maximize) constructor

Method Summary

double	getBestObjectiveValue()
double	getObjectiveTarget() the target for the objective function: we are searching for a solution at least as good as this (tentative bound)
double	getObjectiveValue() v1.0 accessing the objective value of an optimization problem (note that the objective value may not be instantiated, while all other variables are)
void	initBounds() initialization of the optimization bound data structure
void	postDynamicCut() we use targetBound data structures for the optimization cuts
void	postTargetBound() propagating the optimization cuts from the new target bounds
void	postTargetLowerBound()
void	postTargetUpperBound()
void	recordSolution() TODO
void	setBound() resetting the optimization bounds
void	setTargetBound() resetting the values of the target bounds (bounds for the remaining search)
protected void	setTargetLowerBound()
protected void	setTargetUpperBound()

Methods inherited from class choco.search.AbstractGlobalSearchSolver

endTreeNode, endTreeSearch, getEncounteredLimit, incrementalRun, isEncounteredLimit, newTreeNode, newTreeSearch, nextSolution, popTrace, popTraceUntil, printRuntimeStatistics, pushTrace, run, setLoggingMaxDepth, topTrace

Methods inherited from class choco.AbstractSolver

existsSolution, makeSolutionFromCurrentState, restoreBestSolution, showSolution, storeSolution

Methods inherited from class choco.AbstractEntity

getProblem, pretty

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

doMaximize

public boolean doMaximize

a boolean indicating whether we want to maximize (true) or minize (false) the objective variable

objective

public RealVar objective

the variable modelling the objective value

lowerBound

public double lowerBound

the lower bound of the objective value. This value comes from the problem definition; it is strengthened by the search history (solutions found & no-goods)

upperBound

public double upperBound

the upper bound of the objective value This value comes from the problem definition; it is strengthened by the search history (solutions found & no-goods)

targetUpperBound

public double targetUpperBound

a tentative upper bound

targetLowerBound

public double targetLowerBound

a tentative lower bound

Constructor Detail

AbstractRealOptimize

protected AbstractRealOptimize(RealVar obj,
                               boolean maximize)

constructor

Parameters:

obj - the objective variable

maximize - maximization or minimization ?

Method Detail

getObjectiveValue

public double getObjectiveValue()

v1.0 accessing the objective value of an optimization problem (note that the objective value may not be instantiated, while all other variables are)

Returns:

the current objective value

getBestObjectiveValue

public double getBestObjectiveValue()

getObjectiveTarget

public double getObjectiveTarget()

the target for the objective function: we are searching for a solution at least as good as this (tentative bound)

initBounds

public void initBounds()

initialization of the optimization bound data structure

recordSolution

public void recordSolution()

TODO

Overrides:

recordSolution in class AbstractGlobalSearchSolver

setBound

public void setBound()

resetting the optimization bounds

setTargetBound

public void setTargetBound()

resetting the values of the target bounds (bounds for the remaining search)

setTargetLowerBound

protected void setTargetLowerBound()

setTargetUpperBound

protected void setTargetUpperBound()

postTargetBound

public void postTargetBound()
                     throws ContradictionException

propagating the optimization cuts from the new target bounds

Throws:

ContradictionException

postTargetLowerBound

public void postTargetLowerBound()
                          throws ContradictionException

Throws:

ContradictionException

postTargetUpperBound

public void postTargetUpperBound()
                          throws ContradictionException

Throws:

ContradictionException

postDynamicCut

public void postDynamicCut()
                    throws ContradictionException

we use targetBound data structures for the optimization cuts

Overrides:

postDynamicCut in class AbstractGlobalSearchSolver

Throws:

ContradictionException