[jgap-users] please help with cusotm constraintchecker asap
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[jgap-users] please help with cusotm constraintchecker asap
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From: Samik G. <sam...@gm...> - 2006-05-23 20:26:04
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hi all,
I owuld like to get your help in building a custom constraintchecker. I hav=
e
built my class and added its instance to the conf objet.
However, when I run, its gives the following error
org.jgap.InvalidConfigurationException: The gene type
org.jgap.impl.IntegerGene is not allowed to be used in the chromosome due t=
o
the constraint checker used.
please find attahced my code for custom constraint checker as well as the
code for building the sample chromosome.
I would like to mention here that I am checking over the entire chromosome
in the verify method rather than on the genes alone.
---------------------------------------------------
//custom checker code
public class ZOConstraintChecker implements IGeneConstraintChecker{
private OptimizationParameters op;
private Class m_forbidden;
public ZOConstraintChecker(OptimizationParameters op) {
this.op =3D op;
m_forbidden =3D Integer.class;
}
public boolean verify(Gene a, Object value, IChromosome chrome, int
geneIndex ) {
if (m_forbidden =3D=3D null) {
return true;
}
boolean status =3D true;
int [][] X =3D new int[op.getnBSC()][op.getnBSC()];
int [][] Z =3D new int[op.getnCell()][op.getnCell()];
int [][] U =3D new int[op.getnBSC()][op.getnLPP()];
int [][] V =3D new int[op.getnCell()][op.getnBSC()];
int [][] Y =3D new int[op.getnCell()][op.getnCell()];
int nCell =3D op.getnCell();
int nBSC =3D op.getnBSC();
int nLPP =3D op.getnLPP();
int nZone =3D nCell;
for(int l=3D0; l < nCell; l++) {
for(int n=3D0; n < nZone; n++) {
Y[l][n] =3D0;
}
}
Gene[] geneList =3D chrome.getGenes();
//populate Z and Y
int zone,z;
for(int cellGene =3D 0; cellGene < nCell; cellGene++) {
zone =3D ((Integer)geneList[cellGene].getAllele()).intValue();
Y[cellGene][zone-1] =3D 1;
for(int j=3D0; j < nCell; j++) {
z =3D ((Integer)geneList[j].getAllele()).intValue();
if(zone=3D=3Dz)
Z[cellGene][j] =3D 0;
else
Z[cellGene][j] =3D 1;
}
}
int counter =3D nCell;
//populate X
int bscGene, zoneBSC, zBSC;
for(bscGene =3D 0; bscGene < nBSC; bscGene++) {
zoneBSC =3D ((Integer)geneList[counter +
bscGene].getAllele()).intValue();
for(int j=3D0; j < nBSC; j++) {
zBSC =3D ((Integer)geneList[counter +
j].getAllele()).intValue();
if(zoneBSC=3D=3DzBSC)
X[bscGene][j] =3D 0;
else
X[bscGene][j] =3D 1;
}
}
//populate V
int val;
counter =3D nCell + nBSC;
for(int i =3D 0; i < nCell; i++) {
for(int j=3D0; j < nBSC; j++) {
val =3D ((Integer)geneList[counter].getAllele()).intValue(=
);
counter++;
V[i][j] =3D val;
}
}
//populate U
counter =3D+ nCell*nBSC;
for(int i =3D 0; i < nBSC; i++) {
for(int j=3D0; j < nLPP; j++) {
val =3D ((Integer)geneList[counter].getAllele()).intValue=
();
counter++;
U[i][j] =3D val;
}
}
// now check all the constraints as defined in eqn. 11 to 20 in the
report
// note that consts 13 and 14 are captured in the encoding itself
//const 11
int sumL=3D0;
for(int l=3D0; l < nCell; l++) {
sumL=3D0;
for(int j=3D0; j < nBSC; j++) {
sumL+=3DV[l][j];
}
if(sumL!=3D1) {
status =3D false;
return status;
}
else status =3D true;
}
//const 12
int sumI=3D0;
for(int i=3D0; i < nBSC; i++) {
sumI=3D0;
for(int k=3D0; k < nLPP; k++) {
sumI+=3DU[i][k];
}
if(sumI!=3D1) {
status =3D false;
return status;
}
else status =3D true;
}
//const 13
for(int l=3D0; l < nCell; l++) {
sumI=3D0;
for(int n=3D0; n < nZone; n++) {
sumI+=3DY[l][n];
}
if(sumI!=3D1) {
status =3D false;
return status;
}
else status =3D true;
}
//const 14
int RHS, LHS=3D0;
for(int l=3D0; l < nCell; l++) {
for(int m=3D0; m < nCell; m++) {
LHS=3D1 - Z[l][m];
RHS=3D0;
for(int n=3D0; n < nZone; n++) {
RHS+=3DY[l][n]*Y[m][n];
}
if(LHS !=3D RHS) {
status =3D false;
return status;
}
else status =3D true;
}
}
//const 15
RHS=3D0;
LHS=3D0;
for(int i=3D0; i < nBSC; i++) {
for(int j=3D0; j < nBSC; j++) {
LHS=3D1 - X[i][j];
RHS=3D0;
for(int k=3D0; k < nLPP; k++) {
RHS+=3DU[i][k]*U[j][k];
}
if(LHS > RHS) {
status =3D false;
return status;
}
else status =3D true;
}
}
//const 16
for(int l=3D0; l < nCell; l++) {
for(int m=3D0; m < nCell; m++) {
LHS=3DZ[l][m];
RHS=3D0;
for(int i=3D0; i < nBSC; i++) {
for(int j=3D0; j < nBSC; j++) {
RHS+=3D V[l][i]*V[m][j]*X[i][j];
}
}
if(LHS !=3D RHS) {
status =3D false;
return status;
}
else status =3D true;
}
}
//const 17
double suml=3D0.0;
double[] alphaCell =3D new double[nCell];
for(int l=3D0; l < nCell; l++) {
suml =3D0.0;
for(int m=3D0; m < nCell; m++) {
suml +=3D op.getLambdaCell()[m]*(1-Z[l][m]);
}
alphaCell[l]=3D suml;
if(alphaCell[l] > op.getPageLoadCell()[l]) {
status =3D false;
return status;
}
else status =3D true;
}
//const 18
for(int i=3D0; i < nBSC; i++) {
suml =3D0.0;
for(int j=3D0; j < nBSC; j++) {
for(int l =3D0; l < nCell; l++) {
suml+=3DalphaCell[l]*V[l][j];
}
suml*=3D(1 - X[i][j]);
}
if(suml > op.getPageLoadBSC()[i]) {
status =3D false;
return status;
}
else status =3D true;
}
//const 19
double sumCap=3D0.0;
for(int i =3D0; i < nBSC; i++) {
sumCap=3D0.0;
for(int l=3D0; l < nCell; l++) {
sumCap+=3D op.getBhcaCell()[l]*V[l][i];
}
if(sumCap > op.getBhcaBSC()[i]) {
status =3D false;
return status;
}
else status =3D true;
}
//const 20
double sumLHS=3D0.0;
for(int k =3D0; k < nLPP; k++) {
sumLHS=3D0.0;
for(int i=3D0;i < nBSC; i++) {
for(int l=3D0; l < nCell; l++)
sumLHS +=3D op.getBhcaCell()[l]*V[l][i];
sumLHS*=3DU[i][k];
}
if(sumLHS > op.getBhcaLPP()[k]) {
status =3D false;
return status;
}
else status =3D true;
}
return status;
}
}
-------------------------------------------------------
//sample chromosome code and conf init code
public Chromosome generateSampleChromosome(Gene[] sampleGenes) {
RandomGenerator rng =3D new GaussianRandomGenerator();
int cell=3D0;
for(cell=3D0; cell < op.getnCell(); cell++) {
sampleGenes[cell] =3D new IntegerGene(1,op.getnCell());
sampleGenes[cell].setToRandomValue(rng);
}
int bscIndex =3D cell;
for(int bsc=3D0; bsc < op.getnBSC(); bsc++) {
sampleGenes[bscIndex + bsc] =3D new IntegerGene(1,op.getnBSC())=
;
sampleGenes[bscIndex + bsc].setToRandomValue(rng);
}
int geneCounter =3D op.getnCell()+ op.getnBSC();
int counter =3D0;
for(counter=3D0; counter < op.getnCell()*op.getnBSC(); counter++) {
sampleGenes[geneCounter + counter] =3D (new IntegerGene(0,1));
sampleGenes[geneCounter + counter].setToRandomValue(rng);
}
geneCounter =3D geneCounter + op.getnCell()*op.getnBSC();
for(counter=3D0; counter < op.getnBSC()*op.getnLPP(); counter++) {
sampleGenes[geneCounter + counter] =3D new IntegerGene(0,1);
sampleGenes[geneCounter + counter].setToRandomValue(rng);
}
Chromosome sampleChrome =3D new Chromosome(sampleGenes);
return sampleChrome;
}
public void generateSolution() throws Exception {
Configuration conf =3D new DefaultConfiguration();
conf.setPreservFittestIndividual(true);
// Set the fitness function we want to use, which is our
// MinimizingMakeChangeFitnessFunction. We construct it with
// the target amount of change passed in to this method.
// ---------------------------------------------------------
ZOFitnessFunction zoFunc =3D
new ZOFitnessFunction(op);
conf.setFitnessFunction(zoFunc);
// Now we need to tell the Configuration object how we want our
// Chromosomes to be setup. We do that by actually creating a
// sample Chromosome and then setting it on the Configuration
// object.
Gene[] sampleGenes =3D new Gene[op.getnCell() + op.getnBSC()+
op.getnCell()* op.getnBSC() + op.getnBSC()*op.getnLPP()];
Chromosome sampleChromosome =3DgenerateSampleChromosome(sampleGenes=
);
ZOConstraintChecker zoConst =3D new ZOConstraintChecker(op);
sampleChromosome.setConstraintChecker(zoConst);
conf.setPopulationSize(GASolver.MAX_POPULATION_SIZE);
conf.setSampleChromosome(sampleChromosome);
......
-------------------------------------------------------------------
Eagerly waiting for your help,
SAmik
--=20
Samik Ghosh
Center For Research In Wireless Mobility And Networking (CreWMaN)
http://crewman.uta.edu/~sghosh
Department of Computer Science & Engineering
University of Texas at Arlington
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