n<-300

m1<-1000

p<-matrix(0,nrow=n,ncol=n)
for(i in 1:19){
p[i,i+1]<-1
}
for(i in 21:39){
p[i,i+1]<-1
}
for(i in 41:59){
p[i,i+1]<-1
}
for(i in 61:79){
p[i,i+1]<-1
}
for(i in 81:99){
p[i,i+1]<-1
} 
for(i in 101:119){
p[i,i+1]<-1
}
p[20,121]<-1
p[40,121]<-1
for(i in 121:149){
p[i,i+1]<-1
}
p[60,151]<-1
p[80,151]<-1
for(i in 151:179){
p[i,i+1]<-1
}
p[100,181]<-1
p[120,181]<-1
for(i in 181:209){
p[i,i+1]<-1
}
p[40,282]<-1
p[282,211]<-1
for(i in 211:214){
p[i,i+1]<-1
}
p[80,283]<-1
p[283,216]<-1
for(i in 216:219){
p[i,i+1]<-1
}
p[120,284]<-1
p[284,221]<-1
for(i in 221:224){
p[i,i+1]<-1
}
p[215,226]<-1
for(i in 226:234){
p[i,i+1]<-1
}
p[220,236]<-1
for(i in 236:244){
p[i,i+1]<-1
}
p[225,246]<-1
for(i in 246:254){
p[i,i+1]<-1
}
p[235,256]<-1
for(i in 256:262){
p[i,i+1]<-1
}
p[245,264]<-1
for(i in 264:271){
p[i,i+1]<-1
}
p[255,273]<-1
for(i in 273:279){
p[i,i+1]<-1
}
p[263,281]<-1
p[272,281]<-1
p[280,281]<-1
p[215,285]<-1
p[285,250]<-1
p[220,286]<-1
p[286,264]<-1
p[225,287]<-1
p[287,273]<-1
p[288,289]<-1
p[288,290]<-1
p[289,291]<-1
p[289,292]<-1
p[290,293]<-1
p[290,294]<-1
p[291,295]<-1
p[292,296]<-1
p[293,297]<-1
p[294,298]<-1
p[295,299]<-1
p[296,299]<-1
p[297,300]<-1
p[298,300]<-1
 
duration<-matrix(0,nrow=m1,ncol=n)
for(i in 1:m1){
duration[i,]<-rnorm(n,50,10)
}

set.seed(1)
actual.duration<-rnorm(n,50,10)+rnorm(n,7,3) 

time<-2591.448