Prolog-consult(+File)

From

http://www.lix.polytechnique.fr/~catuscia/teaching/prolog/Manual/sec-3.2.html 

consult(+File) Read File as a Prolog source file. File may be a list of files, in which case all members are consulted in turn. File may start with the csh(1) special sequences ~, ~ and $. File may also be library(Name), in which case the libraries are searched for a file with the specified name. See also library_directory/1 and file_search_path/2. consult/1 may be abbreviated by just typing a number of file names in a list. Examples: ?- consult(load). % consult load or load.pl ?- [library(quintus)]. % load Quintus compatibility library Equivalent to load_files(Files, []).

Assign-Solution found

int nbFlt = …;
int nbGate = …;

range Gate 1 .. nbGate;
range Flt 1 .. nbFlt;

var
   int assign[Flt,Gate] in 0..1,
   int y[Flt,Flt] in 0..1;

float+ arrtm[Flt] = …;
float+ dptm[Flt] = …;
//var float+ interval[Flt, Flt];
                     
minimize
     sum (i in Flt, j in Flt)( y[i,j] )
 
subject to {
   
           forall(i in Flt, j in Flt: i j )
             {
              //i j;
              sum(k in Gate)assign[i,k] * assign[j,k] = y[i,j];        
               };
               
            forall(i in Flt)
            sum(k in  Gate) assign[i,k] = 1;
                    
           
           //forall(i in Flt, j in Flt)
          //   i j;
                     
           };

Who could figure out the question in the model?

1. assign.mod

int nbFlt = …;
int nbGate = …;

range Gate 1 .. nbGate;
range Flt 1 .. nbFlt;
range Boolean 0..1;

float+ arrtm[Flt] = …;
float+ dptm[Flt] = …;

                    
var Boolean assign[Flt,Gate];
var Boolean y[Flt,Flt];
var float interval[Flt,Flt];                      

minimize

     sum (i in Flt, j in Flt) y[i,j] * (-1) * interval[i,j]
 
subject to {
           forall(i in Flt, j in Flt)
           i j;
          
           forall(i in Flt, j in Flt)
           interval[i,j] = arrtm[j] - dptm[i];
          
           forall(i in Flt)
           sum(k in  Gate) assign[i,k] = 1;
          
           forall(i in Flt, j in Flt)
           sum(k in Gate)assign[i,k] * assign[j,k] = y[i,j]
           };

2. exp.mod

int nbFlt = …;
int nbGate = …;

range Gate 1 .. nbGate;
range Flt 1 .. nbFlt;

var
   int assign[Flt,Gate] in 0..1,
   int y[Flt,Flt] in 0..1;

float+ arrtm[Flt] = …;
float+ dptm[Flt] = …;

                

minimize
     sum (i in Flt, j in Flt) y[i,j]
 
subject to {
           forall(i in Flt, j in Flt)
           i j;
           forall(i in Flt)
           sum(k in  Gate) assign[i,k] = 1;
           forall(i in Flt, j in Flt)
               {
               i j;
               sum(k in Gate)assign[i,k] * assign[j,k] = y[i,j];       
               };
           };
          

Null deviance reference

http://tolstoy.newcastle.edu.au/R/help/99a/0242.htm

https://stat.ethz.ch/pipermail/r-help/1999-February/003500.html

https://stat.ethz.ch/pipermail/r-help/1999-February/003492.html 

http://zoonek2.free.fr/UNIX/48_R/12.html 

Logistic-Poisson

emoticon Dose<-c(0,0.3,0.35,0.45,0.6,0.75,1.0,1.5)
MiceExposed<-c(101,443,200,103,66,75,31,11)
Incidence<-c(1,5,0,2,2,12,21,11)
NoneIncidence<-MiceExposed-Incidence
glm(Dose~cbind(Incidence,NoneIncidence))
rate<-Incidence/MiceExposed
glm(rate~Dose,binomial)
plot(Dose,rate)
lines(Dose,rate)
plot(MiceExposed,Incidence)
#lines(MiceExposed,Incidence)
X<-cbind(Incidence,NoneIncidence)
glm(X~Dose,family=binomial)
glm(cbind(Incidence,NoneIncidence)~Dose,binomial)
glm(Dose~cbind(Incidence,NoneIncidence))
summary(glm(cbind(Incidence,NoneIncidence)~Dose,binomial))
fitted(glm(cbind(Incidence,NoneIncidence)~Dose,binomial))
res<-resid(glm(cbind(Incidence,NoneIncidence)~Dose,binomial))
plot(Dose,res)
#plot(fitted,res)
qqnorm(res)
fitty<-predict(glm(cbind(Incidence,NoneIncidence)~Dose,binomial))
plot(fitty,res)

#ERROR glm(Dose~cbind(Incidence,MiceExposed),family=binomial)#eval(expr,
# envir, enclos) : y values must be 0 <= y <= 1

glm(rate~Dose,binomial)#Warning message: In eval(expr, envir, enclos) :
# non-integer #successes in a binomial glm!
curve(exp(9.016*x-8.326)/(1+exp(9.016*x-8.326)),add=TRUE, 0, 1.6)
summary(glm(rate~Dose,binomial))

#liver CANCER
Dose<-c(0,0.3,0.35,0.45,0.6,0.75,1.0,1.5)
MiceExposed<-c(555,2014,1102,550,441,382,213,211)
Incidence<-c(6,34,20,15,13,17,19,24)
NoneIncidence<-MiceExposed-Incidence
glm(Dose~cbind(Incidence,NoneIncidence))
rate<-Incidence/MiceExposed
glm(rate~Dose,binomial)
plot(Dose,rate)
lines(Dose,rate)
plot(MiceExposed,Incidence)
X<-cbind(Incidence,NoneIncidence)
glm(X~Dose,family=binomial)
glm(cbind(Incidence,NoneIncidence)~Dose,binomial)
glm(Dose~cbind(Incidence,NoneIncidence))
summary(glm(cbind(Incidence,NoneIncidence)~Dose,binomial))
fitted(glm(cbind(Incidence,NoneIncidence)~Dose,binomial))
res<-resid(glm(cbind(Incidence,NoneIncidence)~Dose,binomial))
plot(Dose,res)
qqnorm(res)
fitty<-predict(glm(cbind(Incidence,NoneIncidence)~Dose,binomial))
plot(fitty,res)
glm(rate~Dose,binomial)
summary(glm(rate~Dose,binomial))

#4.13
xDose<-c(0,80,160,235,310,0,80,160,235,310,0,80,160,235,310,0,80,160,235,310,0,80,160,235,310,0,80,160,235,310,0,80,160,235,310,0,80,160,235,310,0,80,160,235,310,0,80,160,235,310)
yNumber<-c(27,33,29,23,6,32,33,29,21,6,34,35,23,7,7,33,33,27,12,0,36,36,30,27,15,34,26,31,16,5,33,27,30,13,6,30,31,26,15,4,24,32,29,21,6,31,29,29,17,5)
plot(xDose,yNumber)
#lines(xDose,yNumber)
glm(yNumber~xDose,poisson)
summary(glm(yNumber~xDose,poisson))
anova(glm(yNumber~xDose,poisson))
res<-resid(glm(yNumber~xDose,poisson))
fit<-fitted(glm(yNumber~xDose,poisson))
plot(fit,res)
plot(xDose,res)
qqnorm(res)

curve(x^3-3*x, -2, 2)
curve(x^2-3, add = TRUE, col = "red")

glm(yNumber~xDose^2+xDose,poisson)
summary(glm(yNumber~xDose^2+xDose,poisson))
anova(glm(yNumber~xDose^2+xDose,poisson))
res<-resid(glm(yNumber~xDose^2+xDose,poisson))
fit<-fitted(glm(yNumber~xDose^2+xDose,poisson))
plot(fit,res)
plot(xDose,res)
qqnorm(res)

glm(yNumber~xDose^2+xDose,family=poisson)
summary(glm(yNumber~xDose^2+xDose,poisson))
anova(glm(yNumber~xDose^2+xDose,poisson))
res<-resid(glm(yNumber~xDose^2+xDose,poisson))
fit<-fitted(glm(yNumber~xDose^2+xDose,poisson))
plot(fit,res)
plot(xDose,res)
qqnorm(res)

Assign.dat

nbFlt = 996;
nbGate = 70;

arrtm =
[5,
5,
5.1,
5.15,
5.15,
5.15,
5.3,
5.3,
5.3,
5.3,
5.3,
5.4,
5.4,
5.45,
5.45,
5.45,
5.5,
5.5,
5.55,
5.55,
5.55,
6,
6.05,
6.05,
6.05,
6.05,
6.08,
6.1,
6.1,
6.1,
6.1,
6.1,
6.1,
6.1,
6.1,
6.1,
6.15,
6.15,
6.15,
6.15,
6.15,
6.15,
6.15,
6.15,
6.17,
6.17,
6.17,
6.2,
6.2,
6.2,
6.2,
6.25,
6.25,
6.25,
6.25,
6.25,
6.25,
6.25,
6.3,
6.3,
6.3,
6.3,
6.3,
6.3,
6.3,
6.35,
6.35,
6.35,
6.35,
6.4,
6.4,
6.4,
6.4,
6.4,
6.4,
6.44,
6.45,
6.45,
6.45,
6.48,
6.5,
6.5,
6.5,
6.53,
7,
7,
7,
7.05,
7.2,
7.25,
7.3,
7.3,
7.3,
7.3,
7.3,
7.3,
7.3,
7.3,
7.3,
7.3,
7.35,
7.35,
7.35,
7.35,
7.35,
7.35,
7.35,
7.35,
7.35,
7.35,
7.4,
7.4,
7.4,
7.4,
7.4,
7.4,
7.45,
7.45,
7.45,
7.45,
7.45,
7.45,
7.45,
7.5,
7.5,
7.5,
7.5,
7.5,
7.5,
7.5,
7.54,
7.55,
7.55,
7.55,
7.55,
7.55,
7.55,
7.55,
7.55,
7.56,
7.58,
7.59,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8.05,
8.05,
8.05,
8.05,
8.05,
8.05,
8.05,
8.05,
8.05,
8.05,
8.1,
8.1,
8.1,
8.1,
8.1,
8.15,
8.15,
8.15,
8.15,
8.15,
8.15,
8.15,
8.15,
8.15,
8.17,
8.2,
8.2,
8.2,
8.2,
8.22,
8.25,
8.25,
8.27,
8.3,
8.3,
8.3,
8.3,
8.35,
8.35,
8.35,
8.4,
8.4,
8.45,
8.53,
8.55,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.07,
9.1,
9.1,
9.1,
9.1,
9.1,
9.1,
9.1,
9.1,
9.1,
9.1,
9.1,
9.1,
9.1,
9.1,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.16,
9.2,
9.2,
9.2,
9.2,
9.2,
9.2,
9.2,
9.22,
9.25,
9.25,
9.25,
9.25,
9.25,
9.25,
9.25,
9.26,
9.3,
9.3,
9.3,
9.3,
9.3,
9.3,
9.3,
9.35,
9.35,
9.35,
9.35,
9.35,
9.35,
9.35,
9.35,
9.35,
9.35,
9.4,
9.4,
9.4,
9.4,
9.4,
9.4,
9.4,
9.4,
9.4,
9.4,
9.45,
9.45,
9.45,
9.45,
9.45,
9.55,
9.55,
9.55,
9.55,
9.55,
10,
10,
10,
10.05,
10.05,
10.05,
10.05,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.15,
10.15,
10.15,
10.15,
10.15,
10.15,
10.2,
10.2,
10.2,
10.25,
10.25,
10.25,
10.25,
10.25,
10.3,
10.3,
10.3,
10.3,
10.3,
10.3,
10.3,
10.3,
10.3,
10.34,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.39,
10.4,
10.4,
10.4,
10.4,
10.4,
10.45,
10.45,
10.45,
10.45,
10.45,
10.45,
10.45,
10.45,
10.5,
10.5,
10.5,
10.5,
10.55,
10.55,
10.55,
10.55,
11,
11,
11.05,
11.1,
11.1,
11.1,
11.15,
11.15,
11.16,
11.2,
11.2,
11.25,
11.25,
11.25,
11.25,
11.25,
11.3,
11.3,
11.3,
11.3,
11.3,
11.3,
11.35,
11.35,
11.35,
11.35,
11.39,
11.4,
11.4,
11.4,
11.4,
11.4,
11.4,
11.41,
11.45,
11.45,
11.45,
11.45,
11.45,
11.45,
11.45,
11.45,
11.5,
11.5,
11.52,
11.52,
11.55,
11.55,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12.05,
12.05,
12.05,
12.05,
12.05,
12.05,
12.05,
12.05,
12.05,
12.05,
12.05,
12.05,
12.1,
12.1,
12.1,
12.1,
12.1,
12.1,
12.1,
12.1,
12.1,
12.1,
12.1,
12.15,
12.15,
12.15,
12.15,
12.15,
12.2,
12.2,
12.2,
12.2,
12.2,
12.2,
12.2,
12.2,
12.2,
12.25,
12.3,
12.3,
12.3,
12.3,
12.3,
12.3,
12.3,
12.3,
12.3,
12.3,
12.35,
12.35,
12.35,
12.35,
12.4,
12.4,
12.4,
12.45,
12.45,
12.45,
12.45,
12.5,
12.53,
12.55,
13,
13,
13.05,
13.05,
13.09,
13.1,
13.1,
13.1,
13.1,
13.1,
13.1,
13.1,
13.15,
13.15,
13.15,
13.15,
13.15,
13.15,
13.15,
13.15,
13.18,
13.19,
13.19,
13.2,
13.2,
13.2,
13.2,
13.2,
13.2,
13.2,
13.2,
13.21,
13.21,
13.23,
13.25,
13.25,
13.25,
13.25,
13.25,
13.25,
13.25,
13.25,
13.25,
13.3,
13.3,
13.3,
13.3,
13.3,
13.3,
13.3,
13.3,
13.31,
13.35,
13.35,
13.35,
13.35,
13.35,
13.35,
13.35,
13.35,
13.35,
13.35,
13.35,
13.4,
13.4,
13.4,
13.4,
13.4,
13.4,
13.4,
13.4,
13.4,
13.4,
13.4,
13.45,
13.45,
13.45,
13.45,
13.45,
13.45,
13.47,
13.5,
13.5,
13.5,
13.5,
13.55,
13.55,
14,
14,
14.15,
14.15,
14.15,
14.15,
14.15,
14.2,
14.2,
14.2,
14.2,
14.2,
14.25,
14.25,
14.25,
14.25,
14.25,
14.25,
14.27,
14.27,
14.27,
14.28,
14.29,
14.3,
14.3,
14.3,
14.3,
14.3,
14.3,
14.3,
14.3,
14.3,
14.32,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.4,
14.4,
14.4,
14.4,
14.4,
14.4,
14.4,
14.44,
14.45,
14.45,
14.45,
14.45,
14.45,
14.45,
14.45,
14.45,
14.45,
14.45,
14.45,
14.5,
14.5,
14.5,
14.5,
14.54,
14.55,
14.55,
14.55,
14.55,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15.01,
15.05,
15.05,
15.05,
15.05,
15.05,
15.05,
15.1,
15.1,
15.1,
15.1,
15.15,
15.15,
15.15,
15.15,
15.17,
15.17,
15.2,
15.25,
15.3,
15.3,
15.3,
15.32,
15.35,
15.35,
15.4,
15.4,
15.4,
15.4,
15.4,
15.45,
15.45,
15.45,
15.45,
15.45,
15.5,
15.55,
15.55,
15.59,
16,
16.05,
16.1,
16.15,
16.15,
16.2,
16.24,
16.25,
16.25,
16.25,
16.25,
16.3,
16.3,
16.3,
16.3,
16.3,
16.35,
16.35,
16.35,
16.35,
16.35,
16.35,
16.39,
16.4,
16.4,
16.4,
16.4,
16.4,
16.4,
16.4,
16.4,
16.4,
16.4,
16.4,
16.45,
16.45,
16.45,
16.45,
16.45,
16.45,
16.45,
16.45,
16.45,
16.5,
16.5,
16.5,
16.5,
16.5,
16.5,
16.5,
16.5,
16.5,
16.51,
16.55,
16.55,
16.55,
16.55,
16.55,
16.55,
17,
17,
17,
17,
17,
17,
17,
17,
17,
17,
17,
17.05,
17.05,
17.05,
17.05,
17.1,
17.1,
17.12,
17.15,
17.15,
17.15,
17.2,
17.2,
17.25,
17.25,
17.25,
17.3,
17.35,
17.35,
17.35,
17.35,
17.35,
17.39,
17.39,
17.39,
17.4,
17.4,
17.4,
17.4,
17.4,
17.4,
17.4,
17.42,
17.44,
17.45,
17.45,
17.45,
17.45,
17.45,
17.45,
17.45,
17.45,
17.49,
17.5,
17.5,
17.5,
17.5,
17.5,
17.53,
17.55,
17.55,
17.55,
17.55,
17.55,
17.55,
17.55,
17.55,
17.55,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18.05,
18.05,
18.05,
18.05,
18.05,
18.05,
18.05,
18.05,
18.05,
18.05,
18.05,
18.1,
18.1,
18.1,
18.1,
18.1,
18.1,
18.1,
18.1,
18.1,
18.1,
18.1,
18.12,
18.15,
18.15,
18.15,
18.15,
18.15,
18.15,
18.2,
18.2,
18.2,
18.2,
18.2,
18.2,
18.2,
18.25,
18.25,
18.25,
18.3,
18.3,
18.4,
18.4,
18.45,
18.55,
19.4,
19.4,
19.4,
19.4,
19.4,
19.45,
19.45,
19.48,
19.5,
19.5,
19.5,
19.5,
19.5,
19.5,
19.52,
19.53,
19.55,
19.55,
19.55,
19.55,
19.55,
19.55,
19.55,
19.55,
19.55,
19.55,
19.55,
20,
20,
20,
20,
20,
20,
20,
20,
20.05,
20.05,
20.05,
20.05,
20.05,
20.05,
20.05,
20.1,
20.1,
20.1,
20.1,
20.1,
20.1,
20.1,
20.1,
20.15,
20.15,
20.15,
20.15,
20.15,
20.15,
20.15,
20.15,
20.2,
20.2,
20.2,
20.2,
20.2,
20.25,
20.25,
20.25,
20.25,
20.25,
20.25,
20.25,
20.25,
20.25,
20.25,
20.25,
20.25,
20.27,
20.3,
20.3,
20.3,
20.3,
20.3,
20.35,
21.45,
21.47,
21.52,
21.52,
21.55,
21.55,
21.55,
21.55,
22.3,
22.59];

dptm = [6,
6,
6.1,
6.15,
6.15,
6.15,
6.3,
6.3,
6.3,
6.3,
6.3,
6.4,
6.4,
6.45,
6.45,
6.45,
6.5,
6.5,
6.55,
6.55,
6.55,
7,
7.05,
7.05,
7.05,
7.05,
7.08,
7.1,
7.1,
7.1,
7.1,
7.1,
7.1,
7.1,
7.1,
7.1,
7.15,
7.15,
7.15,
7.15,
7.15,
7.15,
7.15,
7.15,
7.17,
7.17,
7.17,
7.2,
7.2,
7.2,
7.2,
7.25,
7.25,
7.25,
7.25,
7.25,
7.25,
7.25,
7.3,
7.3,
7.3,
7.3,
7.3,
7.3,
7.3,
7.35,
7.35,
7.35,
7.35,
7.4,
7.4,
7.4,
7.4,
7.4,
7.4,
7.44,
7.45,
7.45,
7.45,
7.48,
7.5,
7.5,
7.5,
7.53,
8,
8,
8,
8.05,
8.2,
8.25,
8.3,
8.3,
8.3,
8.3,
8.3,
8.3,
8.3,
8.3,
8.3,
8.3,
8.35,
8.35,
8.35,
8.35,
8.35,
8.35,
8.35,
8.35,
8.35,
8.35,
8.4,
8.4,
8.4,
8.4,
8.4,
8.4,
8.45,
8.45,
8.45,
8.45,
8.45,
8.45,
8.45,
8.5,
8.5,
8.5,
8.5,
8.5,
8.5,
8.5,
8.54,
8.55,
8.55,
8.55,
8.55,
8.55,
8.55,
8.55,
8.55,
8.56,
8.58,
8.59,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.05,
9.1,
9.1,
9.1,
9.1,
9.1,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.15,
9.17,
9.2,
9.2,
9.2,
9.2,
9.22,
9.25,
9.25,
9.27,
9.3,
9.3,
9.3,
9.3,
9.35,
9.35,
9.35,
9.4,
9.4,
9.45,
9.53,
9.55,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10.05,
10.05,
10.05,
10.05,
10.05,
10.05,
10.05,
10.05,
10.05,
10.05,
10.05,
10.05,
10.05,
10.07,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.1,
10.15,
10.15,
10.15,
10.15,
10.15,
10.15,
10.15,
10.15,
10.15,
10.15,
10.15,
10.15,
10.16,
10.2,
10.2,
10.2,
10.2,
10.2,
10.2,
10.2,
10.22,
10.25,
10.25,
10.25,
10.25,
10.25,
10.25,
10.25,
10.26,
10.3,
10.3,
10.3,
10.3,
10.3,
10.3,
10.3,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.35,
10.4,
10.4,
10.4,
10.4,
10.4,
10.4,
10.4,
10.4,
10.4,
10.4,
10.45,
10.45,
10.45,
10.45,
10.45,
10.55,
10.55,
10.55,
10.55,
10.55,
11,
11,
11,
11.05,
11.05,
11.05,
11.05,
11.1,
11.1,
11.1,
11.1,
11.1,
11.1,
11.1,
11.1,
11.15,
11.15,
11.15,
11.15,
11.15,
11.15,
11.2,
11.2,
11.2,
11.25,
11.25,
11.25,
11.25,
11.25,
11.3,
11.3,
11.3,
11.3,
11.3,
11.3,
11.3,
11.3,
11.3,
11.34,
11.35,
11.35,
11.35,
11.35,
11.35,
11.35,
11.35,
11.35,
11.35,
11.35,
11.35,
11.39,
11.4,
11.4,
11.4,
11.4,
11.4,
11.45,
11.45,
11.45,
11.45,
11.45,
11.45,
11.45,
11.45,
11.5,
11.5,
11.5,
11.5,
11.55,
11.55,
11.55,
11.55,
12,
12,
12.05,
12.1,
12.1,
12.1,
12.15,
12.15,
12.16,
12.2,
12.2,
12.25,
12.25,
12.25,
12.25,
12.25,
12.3,
12.3,
12.3,
12.3,
12.3,
12.3,
12.35,
12.35,
12.35,
12.35,
12.39,
12.4,
12.4,
12.4,
12.4,
12.4,
12.4,
12.41,
12.45,
12.45,
12.45,
12.45,
12.45,
12.45,
12.45,
12.45,
12.5,
12.5,
12.52,
12.52,
12.55,
12.55,
13,
13,
13,
13,
13,
13,
13,
13,
13,
13,
13,
13,
13,
13,
13,
13,
13,
13.05,
13.05,
13.05,
13.05,
13.05,
13.05,
13.05,
13.05,
13.05,
13.05,
13.05,
13.05,
13.1,
13.1,
13.1,
13.1,
13.1,
13.1,
13.1,
13.1,
13.1,
13.1,
13.1,
13.15,
13.15,
13.15,
13.15,
13.15,
13.2,
13.2,
13.2,
13.2,
13.2,
13.2,
13.2,
13.2,
13.2,
13.25,
13.3,
13.3,
13.3,
13.3,
13.3,
13.3,
13.3,
13.3,
13.3,
13.3,
13.35,
13.35,
13.35,
13.35,
13.4,
13.4,
13.4,
13.45,
13.45,
13.45,
13.45,
13.5,
13.53,
13.55,
14,
14,
14.05,
14.05,
14.09,
14.1,
14.1,
14.1,
14.1,
14.1,
14.1,
14.1,
14.15,
14.15,
14.15,
14.15,
14.15,
14.15,
14.15,
14.15,
14.18,
14.19,
14.19,
14.2,
14.2,
14.2,
14.2,
14.2,
14.2,
14.2,
14.2,
14.21,
14.21,
14.23,
14.25,
14.25,
14.25,
14.25,
14.25,
14.25,
14.25,
14.25,
14.25,
14.3,
14.3,
14.3,
14.3,
14.3,
14.3,
14.3,
14.3,
14.31,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.35,
14.4,
14.4,
14.4,
14.4,
14.4,
14.4,
14.4,
14.4,
14.4,
14.4,
14.4,
14.45,
14.45,
14.45,
14.45,
14.45,
14.45,
14.47,
14.5,
14.5,
14.5,
14.5,
14.55,
14.55,
15,
15,
15.15,
15.15,
15.15,
15.15,
15.15,
15.2,
15.2,
15.2,
15.2,
15.2,
15.25,
15.25,
15.25,
15.25,
15.25,
15.25,
15.27,
15.27,
15.27,
15.28,
15.29,
15.3,
15.3,
15.3,
15.3,
15.3,
15.3,
15.3,
15.3,
15.3,
15.32,
15.35,
15.35,
15.35,
15.35,
15.35,
15.35,
15.35,
15.35,
15.35,
15.35,
15.4,
15.4,
15.4,
15.4,
15.4,
15.4,
15.4,
15.44,
15.45,
15.45,
15.45,
15.45,
15.45,
15.45,
15.45,
15.45,
15.45,
15.45,
15.45,
15.5,
15.5,
15.5,
15.5,
15.54,
15.55,
15.55,
15.55,
15.55,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16.01,
16.05,
16.05,
16.05,
16.05,
16.05,
16.05,
16.1,
16.1,
16.1,
16.1,
16.15,
16.15,
16.15,
16.15,
16.17,
16.17,
16.2,
16.25,
16.3,
16.3,
16.3,
16.32,
16.35,
16.35,
16.4,
16.4,
16.4,
16.4,
16.4,
16.45,
16.45,
16.45,
16.45,
16.45,
16.5,
16.55,
16.55,
16.59,
17,
17.05,
17.1,
17.15,
17.15,
17.2,
17.24,
17.25,
17.25,
17.25,
17.25,
17.3,
17.3,
17.3,
17.3,
17.3,
17.35,
17.35,
17.35,
17.35,
17.35,
17.35,
17.39,
17.4,
17.4,
17.4,
17.4,
17.4,
17.4,
17.4,
17.4,
17.4,
17.4,
17.4,
17.45,
17.45,
17.45,
17.45,
17.45,
17.45,
17.45,
17.45,
17.45,
17.5,
17.5,
17.5,
17.5,
17.5,
17.5,
17.5,
17.5,
17.5,
17.51,
17.55,
17.55,
17.55,
17.55,
17.55,
17.55,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18.05,
18.05,
18.05,
18.05,
18.1,
18.1,
18.12,
18.15,
18.15,
18.15,
18.2,
18.2,
18.25,
18.25,
18.25,
18.3,
18.35,
18.35,
18.35,
18.35,
18.35,
18.39,
18.39,
18.39,
18.4,
18.4,
18.4,
18.4,
18.4,
18.4,
18.4,
18.42,
18.44,
18.45,
18.45,
18.45,
18.45,
18.45,
18.45,
18.45,
18.45,
18.49,
18.5,
18.5,
18.5,
18.5,
18.5,
18.53,
18.55,
18.55,
18.55,
18.55,
18.55,
18.55,
18.55,
18.55,
18.55,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19.05,
19.05,
19.05,
19.05,
19.05,
19.05,
19.05,
19.05,
19.05,
19.05,
19.05,
19.1,
19.1,
19.1,
19.1,
19.1,
19.1,
19.1,
19.1,
19.1,
19.1,
19.1,
19.12,
19.15,
19.15,
19.15,
19.15,
19.15,
19.15,
19.2,
19.2,
19.2,
19.2,
19.2,
19.2,
19.2,
19.25,
19.25,
19.25,
19.3,
19.3,
19.4,
19.4,
19.45,
19.55,
20.4,
20.4,
20.4,
20.4,
20.4,
20.45,
20.45,
20.48,
20.5,
20.5,
20.5,
20.5,
20.5,
20.5,
20.52,
20.53,
20.55,
20.55,
20.55,
20.55,
20.55,
20.55,
20.55,
20.55,
20.55,
20.55,
20.55,
21,
21,
21,
21,
21,
21,
21,
21,
21.05,
21.05,
21.05,
21.05,
21.05,
21.05,
21.05,
21.1,
21.1,
21.1,
21.1,
21.1,
21.1,
21.1,
21.1,
21.15,
21.15,
21.15,
21.15,
21.15,
21.15,
21.15,
21.15,
21.2,
21.2,
21.2,
21.2,
21.2,
21.25,
21.25,
21.25,
21.25,
21.25,
21.25,
21.25,
21.25,
21.25,
21.25,
21.25,
21.25,
21.27,
21.3,
21.3,
21.3,
21.3,
21.3,
21.35,
22.45,
22.47,
22.52,
22.52,
22.55,
22.55,
22.55,
22.55,
23.3,
23.59];

Assign.mod

int nbFlt = …;
int nbGate = …;

range Gate 1 .. nbGate;
range Flt 1 .. nbFlt;
range Boolean 0..1;

float+ arrtm[Flt] = …;
float+ dptm[Flt] = …;

                     
var Boolean assign[Flt,Gate];
var Boolean y[Flt,Flt];
                        

minimize
     sum (i in Flt, j in Flt) y[i,j] / (arrtm[j] - dptm[i])
 
subject to {
           forall(i in Flt)
           sum(k in  Gate) assign[i,k] = 1;
           forall(j in Flt)
           sum(k in  Gate) assign[j,k] = 1;
           forall(i in Flt, j in Flt)
           sum(k in Gate)assign[i,k] * assign[j,k] = y[i,j];
           forall(i in Flt, j in Flt)
           arrtm[j] - dptm[i] > 0;
           forall(i in Flt, j in Flt)
           i j;
           };

CO-data ONLY used for Experiments

emoticonData ONLY used for Experiments , not for passengers!

Abstracted Data from Continental Ailines at Houston-IAH

       Arr Dep Flt
5 6 4500
5 6 1478
5.1 6.1 408
5.15 6.15 7737
5.15 6.15 3010
5.15 6.15 7188
5.3 6.3 89
5.3 6.3 1032
5.3 6.3 2703
5.3 6.3 2156
5.3 6.3 1438
5.4 6.4 544
5.4 6.4 2582
5.45 6.45 3802
5.45 6.45 3824
5.45 6.45 5670
5.5 6.5 9538
5.5 6.5 2525
5.55 6.55 9514
5.55 6.55 5855
5.55 6.55 1640
6 7 1815
6.05 7.05 2586
6.05 7.05 2885
6.05 7.05 9550
6.05 7.05 2606
6.08 7.08 5931
6.1 7.1 706
6.1 7.1 3060
6.1 7.1 2608
6.1 7.1 2200
6.1 7.1 688
6.1 7.1 1623
6.1 7.1 9508
6.1 7.1 5562
6.1 7.1 5720
6.15 7.15 216
6.15 7.15 4338
6.15 7.15 2318
6.15 7.15 2658
6.15 7.15 776
6.15 7.15 2202
6.15 7.15 2573
6.15 7.15 2524
6.17 7.17 5620
6.17 7.17 7197
6.17 7.17 199
6.2 7.2 5601
6.2 7.2 1590
6.2 7.2 1097
6.2 7.2 403
6.25 7.25 3083
6.25 7.25 1746
6.25 7.25 167
6.25 7.25 1484
6.25 7.25 3095
6.25 7.25 1841
6.25 7.25 679
6.3 7.3 1454
6.3 7.3 586
6.3 7.3 1048
6.3 7.3 626
6.3 7.3 2396
6.3 7.3 2872
6.3 7.3 2339
6.35 7.35 3081
6.35 7.35 282
6.35 7.35 2090
6.35 7.35 1436
6.4 7.4 520
6.4 7.4 258
6.4 7.4 5501
6.4 7.4 3124
6.4 7.4 2891
6.4 7.4 495
6.44 7.44 7044
6.45 7.45 4179
6.45 7.45 2054
6.45 7.45 2220
6.48 7.48 7028
6.5 7.5 2919
6.5 7.5 2618
6.5 7.5 2357
6.53 7.53 332
7 8 3066
7 8 52
7 8 2914
7.05 8.05 2189
7.2 8.2 2799
7.25 8.25 2528
7.3 8.3 1082
7.3 8.3 2887
7.3 8.3 2916
7.3 8.3 1000
7.3 8.3 3078
7.3 8.3 1583
7.3 8.3 9576
7.3 8.3 2274
7.3 8.3 2367
7.3 8.3 5527
7.35 8.35 5641
7.35 8.35 2792
7.35 8.35 2546
7.35 8.35 5524
7.35 8.35 9552
7.35 8.35 2093
7.35 8.35 5932
7.35 8.35 9518
7.35 8.35 1670
7.35 8.35 5739
7.4 8.4 2282
7.4 8.4 2682
7.4 8.4 2853
7.4 8.4 2955
7.4 8.4 9521
7.4 8.4 5752
7.45 8.45 2173
7.45 8.45 9578
7.45 8.45 1622
7.45 8.45 2158
7.45 8.45 2926
7.45 8.45 5503
7.45 8.45 1857
7.5 8.5 1076
7.5 8.5 510
7.5 8.5 9527
7.5 8.5 5731
7.5 8.5 1052
7.5 8.5 1873
7.5 8.5 1679
7.54 8.54 623
7.55 8.55 5502
7.55 8.55 5541
7.55 8.55 5679
7.55 8.55 317
7.55 8.55 2928
7.55 8.55 1668
7.55 8.55 4844
7.55 8.55 5716
7.56 8.56 2254
7.58 8.58 673
7.59 8.59 630
8 9 1058
8 9 875
8 9 232
8 9 2605
8 9 424
8 9 799
8 9 464
8 9 1836
8 9 2906
8 9 3041
8 9 7203
8 9 2615
8 9 1466
8.05 9.05 2559
8.05 9.05 2006
8.05 9.05 2725
8.05 9.05 2089
8.05 9.05 2279
8.05 9.05 1407
8.05 9.05 1858
8.05 9.05 1773
8.05 9.05 5978
8.05 9.05 2277
8.1 9.1 2893
8.1 9.1 5817
8.1 9.1 2160
8.1 9.1 1696
8.1 9.1 762
8.15 9.15 1717
8.15 9.15 2243
8.15 9.15 1714
8.15 9.15 1761
8.15 9.15 1528
8.15 9.15 5694
8.15 9.15 5504
8.15 9.15 864
8.15 9.15 2026
8.17 9.17 826
8.2 9.2 9517
8.2 9.2 1614
8.2 9.2 1495
8.2 9.2 357
8.22 9.22 589
8.25 9.25 739
8.25 9.25 1886
8.27 9.27 756
8.3 9.3 2084
8.3 9.3 497
8.3 9.3 1723
8.3 9.3 2020
8.35 9.35 2027
8.35 9.35 1767
8.35 9.35 1
8.4 9.4 2164
8.4 9.4 463
8.45 9.45 1814
8.53 9.53 1449
8.55 9.55 2833
9 10 2402
9 10 2307
9 10 2502
9 10 342
9 10 2762
9 10 5916
9 10 2002
9 10 2760
9 10 117
9 10 2195
9 10 1481
9 10 2482
9 10 2238
9 10 2211
9 10 2801
9.05 10.05 2069
9.05 10.05 5506
9.05 10.05 2972
9.05 10.05 2333
9.05 10.05 2190
9.05 10.05 441
9.05 10.05 179
9.05 10.05 2768
9.05 10.05 2715
9.05 10.05 2330
9.05 10.05 2210
9.05 10.05 2852
9.05 10.05 542
9.07 10.07 5658
9.1 10.1 3014
9.1 10.1 508
9.1 10.1 1544
9.1 10.1 9580
9.1 10.1 9503
9.1 10.1 2216
9.1 10.1 1768
9.1 10.1 5848
9.1 10.1 2810
9.1 10.1 5925
9.1 10.1 2462
9.1 10.1 2113
9.1 10.1 730
9.1 10.1 212
9.15 10.15 2074
9.15 10.15 5610
9.15 10.15 2106
9.15 10.15 5505
9.15 10.15 3113
9.15 10.15 2389
9.15 10.15 1894
9.15 10.15 2504
9.15 10.15 2698
9.15 10.15 2140
9.15 10.15 2921
9.15 10.15 1476
9.16 10.16 3610
9.2 10.2 2258
9.2 10.2 9513
9.2 10.2 2394
9.2 10.2 2141
9.2 10.2 788
9.2 10.2 2095
9.2 10.2 328
9.22 10.22 2044
9.25 10.25 1448
9.25 10.25 5544
9.25 10.25 3151
9.25 10.25 9522
9.25 10.25 1646
9.25 10.25 1452
9.25 10.25 1690
9.26 10.26 2151
9.3 10.3 1003
9.3 10.3 686
9.3 10.3 3040
9.3 10.3 364
9.3 10.3 3090
9.3 10.3 1508
9.3 10.3 2168
9.35 10.35 2374
9.35 10.35 2299
9.35 10.35 2301
9.35 10.35 2772
9.35 10.35 1595
9.35 10.35 3007
9.35 10.35 2381
9.35 10.35 2057
9.35 10.35 2548
9.35 10.35 1462
9.4 10.4 2041
9.4 10.4 2042
9.4 10.4 1420
9.4 10.4 741
9.4 10.4 2487
9.4 10.4 2451
9.4 10.4 5563
9.4 10.4 3003
9.4 10.4 226
9.4 10.4 40
9.45 10.45 7119
9.45 10.45 9530
9.45 10.45 2405
9.45 10.45 432
9.45 10.45 7
9.55 10.55 5652
9.55 10.55 1597
9.55 10.55 2249
9.55 10.55 5688
9.55 10.55 358
10 11 1549
10 11 2822
10 11 3717
10.05 11.05 478
10.05 11.05 779
10.05 11.05 5723
10.05 11.05 382
10.1 11.1 2977
10.1 11.1 1760
10.1 11.1 517
10.1 11.1 2630
10.1 11.1 2526
10.1 11.1 2845
10.1 11.1 1006
10.1 11.1 1429
10.15 11.15 3102
10.15 11.15 2071
10.15 11.15 9546
10.15 11.15 5643
10.15 11.15 1816
10.15 11.15 5807
10.2 11.2 1769
10.2 11.2 9499
10.2 11.2 884
10.25 11.25 2459
10.25 11.25 5645
10.25 11.25 1455
10.25 11.25 1581
10.25 11.25 73
10.3 11.3 1605
10.3 11.3 489
10.3 11.3 2857
10.3 11.3 305
10.3 11.3 345
10.3 11.3 2142
10.3 11.3 9502
10.3 11.3 9519
10.3 11.3 723
10.34 11.34 5721
10.35 11.35 2060
10.35 11.35 2910
10.35 11.35 1838
10.35 11.35 2831
10.35 11.35 9542
10.35 11.35 9492
10.35 11.35 9541
10.35 11.35 2704
10.35 11.35 1465
10.35 11.35 1806
10.35 11.35 2018
10.39 11.39 2924
10.4 11.4 2196
10.4 11.4 2579
10.4 11.4 286
10.4 11.4 2902
10.4 11.4 1832
10.45 11.45 2001
10.45 11.45 1674
10.45 11.45 2750
10.45 11.45 1727
10.45 11.45 1764
10.45 11.45 2121
10.45 11.45 1990
10.45 11.45 152
10.5 11.5 5663
10.5 11.5 2962
10.5 11.5 2108
10.5 11.5 7189
10.55 11.55 1424
10.55 11.55 499
10.55 11.55 5507
10.55 11.55 7709
11 12 2826
11 12 664
11.05 12.05 2000
11.1 12.1 405
11.1 12.1 267
11.1 12.1 3752
11.15 12.15 2184
11.15 12.15 2998
11.16 12.16 7201
11.2 12.2 2632
11.2 12.2 2804
11.25 12.25 9516
11.25 12.25 3082
11.25 12.25 5537
11.25 12.25 3067
11.25 12.25 5640
11.3 12.3 9505
11.3 12.3 5754
11.3 12.3 5566
11.3 12.3 5570
11.3 12.3 2512
11.3 12.3 5557
11.35 12.35 738
11.35 12.35 1808
11.35 12.35 2596
11.35 12.35 2940
11.39 12.39 1088
11.4 12.4 2917
11.4 12.4 5538
11.4 12.4 1749
11.4 12.4 1629
11.4 12.4 2593
11.4 12.4 2122
11.41 12.41 1523
11.45 12.45 5509
11.45 12.45 2710
11.45 12.45 5568
11.45 12.45 2326
11.45 12.45 1497
11.45 12.45 2361
11.45 12.45 2629
11.45 12.45 2198
11.5 12.5 5948
11.5 12.5 326
11.52 12.52 2083
11.52 12.52 5836
11.55 12.55 379
11.55 12.55 2304
12 13 9543
12 13 2922
12 13 3028
12 13 9491
12 13 3023
12 13 1627
12 13 1404
12 13 2881
12 13 5850
12 13 6945
12 13 592
12 13 1520
12 13 1562
12 13 2841
12 13 5536
12 13 744
12 13 458
12.05 13.05 9524
12.05 13.05 215
12.05 13.05 5607
12.05 13.05 5804
12.05 13.05 2413
12.05 13.05 1695
12.05 13.05 300
12.05 13.05 2980
12.05 13.05 5806
12.05 13.05 5602
12.05 13.05 2105
12.05 13.05 482
12.1 13.1 241
12.1 13.1 2633
12.1 13.1 1464
12.1 13.1 5741
12.1 13.1 9564
12.1 13.1 1548
12.1 13.1 2780
12.1 13.1 1850
12.1 13.1 2159
12.1 13.1 418
12.1 13.1 50
12.15 13.15 5639
12.15 13.15 4916
12.15 13.15 206
12.15 13.15 2791
12.15 13.15 1790
12.2 13.2 5572
12.2 13.2 197
12.2 13.2 1628
12.2 13.2 1840
12.2 13.2 4054
12.2 13.2 4410
12.2 13.2 786
12.2 13.2 532
12.2 13.2 1753
12.25 13.25 554
12.3 13.3 2812
12.3 13.3 2773
12.3 13.3 2824
12.3 13.3 4037
12.3 13.3 2656
12.3 13.3 146
12.3 13.3 5508
12.3 13.3 5534
12.3 13.3 2272
12.3 13.3 2187
12.35 13.35 2217
12.35 13.35 2380
12.35 13.35 2102
12.35 13.35 1092
12.4 13.4 5612
12.4 13.4 3084
12.4 13.4 1576
12.45 13.45 5554
12.45 13.45 2386
12.45 13.45 1993
12.45 13.45 888
12.5 13.5 2643
12.53 13.53 1630
12.55 13.55 1672
13 14 9544
13 14 1473
13.05 14.05 2309
13.05 14.05 5814
13.09 14.09 2479
13.1 14.1 2012
13.1 14.1 2536
13.1 14.1 5953
13.1 14.1 1564
13.1 14.1 1524
13.1 14.1 2555
13.1 14.1 1868
13.15 14.15 5511
13.15 14.15 564
13.15 14.15 2099
13.15 14.15 2056
13.15 14.15 2185
13.15 14.15 137
13.15 14.15 2797
13.15 14.15 62
13.18 14.18 2602
13.19 14.19 725
13.19 14.19 746
13.2 14.2 1541
13.2 14.2 2495
13.2 14.2 2992
13.2 14.2 1557
13.2 14.2 2960
13.2 14.2 5725
13.2 14.2 9554
13.2 14.2 1844
13.21 14.21 2126
13.21 14.21 2191
13.23 14.23 409
13.25 14.25 2908
13.25 14.25 9526
13.25 14.25 9547
13.25 14.25 9572
13.25 14.25 2453
13.25 14.25 3100
13.25 14.25 5567
13.25 14.25 2636
13.25 14.25 9532
13.3 14.3 9493
13.3 14.3 2107
13.3 14.3 1837
13.3 14.3 2385
13.3 14.3 2670
13.3 14.3 697
13.3 14.3 2849
13.3 14.3 1604
13.31 14.31 320
13.35 14.35 2152
13.35 14.35 2631
13.35 14.35 2472
13.35 14.35 2718
13.35 14.35 9545
13.35 14.35 2031
13.35 14.35 2004
13.35 14.35 9573
13.35 14.35 1739
13.35 14.35 158
13.35 14.35 1532
13.4 14.4 1897
13.4 14.4 1799
13.4 14.4 2232
13.4 14.4 2110
13.4 14.4 2945
13.4 14.4 1853
13.4 14.4 1015
13.4 14.4 1470
13.4 14.4 1539
13.4 14.4 419
13.4 14.4 1566
13.45 14.45 5529
13.45 14.45 665
13.45 14.45 1503
13.45 14.45 2811
13.45 14.45 2890
13.45 14