Example Configuration minCSP(50,12,250,32)
## General
## ----------------------------------------------
## Output folder (if not defined as a parameter of csp.bat)
General.Output=output\\RandomCSP

## Problem difinition
## ---------------------------------------------
## Sparse problem CSP(50,12,250/1250,32)
## Number of variables
CSP.NrVariables=50
## Domain size (number of values for a variable)
CSP.DomainSize=12
## Problem density (250/1250)
CSP.Density=0.2
## Problem tightness
CSP.Tightness=0.32
## Number of tests
CPS.NrTests=5
## Generator seed
# CSP.Seed=780921
## Enforce that generated problem will have a solution
CSP.ForceSolutionExistance=true
## Number of kernels (CSP with kernels)
CSP.NrKernels=0
## Size of a kernel (number of variables)
CSP.KernelSize=10
## Density inside a kernel
CSP.KernelDensity=0.43
## Tightness inside a kernel
CSP.KernelTightness=0.55

## Value selection heurisitcs
## --------------------------------------------
## Class
Value.Class=net.sf.cpsolver.ifs.heuristics.GeneralValueSelection
## MPP: limit on number of perturbations (-1 no use)
Value.MPPLimit=-1
## MPP: probability of selection of an initial value
Value.InitialSelectionProb=0.0
## MPP: difference in the number of initial assignments
Value.WeightDeltaInitialAssignments=0.0
## CSP: weight of the number of hard conflicts, weighted by CBS
Value.WeightWeightedConflicts=1.0
## CBS: weight of potential hard conflicts
Value.WeightPotentialConflicts=0.0
## MAC: Probability of selection of a good (not deleted) value
Value.GoodSelectionProb=0.0
## Weight of a hard conflict (variable that has to be unassigned if the value is selected)
Value.WeightConflicts=1.0
## Weight of the number of prior assignements of the value
Value.WeightNrAssignments=0.0
## Weight of a value
Value.WeightValue=1.0
## Random walk (random value selection) probability
Value.RandomWalkProb=0.0
## Length of the tabu-list (0 means no use)
Value.Tabu=0

## Variable selection heuristics
## -------------------------------------------
## Class
Variable.Class=net.sf.cpsolver.ifs.heuristics.GeneralVariableSelection
## Random selection
Variable.RandomSelection=true

## Termination condition
## -------------------------------------------
## Class
Termination.Class=net.sf.cpsolver.ifs.termination.GeneralTerminationCondition
## Maximum number of iterations
Termination.MaxIters=-1
## Timeout in seconds (1 minute)
Termination.TimeOut=60
## MPP: minimal number of perturbations
Termination.MinPerturbances=-1
## Stop search when a complete solution is found
Termination.StopWhenComplete=false

## Solution comparator
## -------------------------------------------
## Class
Comparator.Class=net.sf.cpsolver.ifs.solution.GeneralSolutionComparator

## Extensions
## -------------------------------------------
## Use CBS
Extensions.Classes=net.sf.cpsolver.ifs.extension.ConflictStatistics