n<-100

m1<-1000

p<-matrix(0,nrow=n,ncol=n)
p[1,12]<-1
p[2,13]<-1
p[3,14]<-1
p[4,15]<-1
p[5,16]<-1
p[6,17]<-1
p[7,18]<-1
p[8,19]<-1
p[9,20]<-1
p[9,21]<-1
p[10,22]<-1
p[11,23]<-1
p[12,24]<-1
p[13,24]<-1
p[13,25]<-1
p[14,26]<-1
p[15,26]<-1
p[16,27]<-1
p[17,34]<-1
p[18,28]<-1
p[19,28]<-1
p[20,28]<-1
p[21,29]<-1
p[22,29]<-1
p[23,30]<-1
p[24,31]<-1
p[25,32]<-1
p[26,33]<-1
p[27,34]<-1
p[28,48]<-1
p[28,47]<-1
p[29,45]<-1
p[30,45]<-1
p[31,35]<-1
p[32,35]<-1
p[33,58]<-1
p[33,49]<-1
p[34,58]<-1
p[34,49]<-1
p[35,58]<-1
p[35,49]<-1
p[36,37]<-1
p[36,38]<-1
p[36,39]<-1
p[37,40]<-1
p[38,41]<-1
p[39,42]<-1
p[39,52]<-1
p[40,44]<-1
p[41,43]<-1
p[41,51]<-1
p[42,51]<-1
p[42,43]<-1
p[43,44]<-1
p[44,46]<-1
p[45,55]<-1
p[46,55]<-1
p[47,55]<-1
p[48,50]<-1
p[49,50]<-1
p[50,67]<-1
p[51,54]<-1
p[52,53]<-1
p[52,99]<-1
p[53,54]<-1
p[54,57]<-1
p[54,56]<-1
p[55,56]<-1
p[56,68]<-1
p[56,69]<-1
p[57,70]<-1
p[57,71]<-1
p[57,72]<-1
p[58,59]<-1
p[58,60]<-1
p[58,61]<-1
p[59,64]<-1
p[60,63]<-1
p[61,62]<-1
p[62,66]<-1
p[63,65]<-1
p[64,65]<-1
p[65,84]<-1
p[65,73]<-1
p[66,84]<-1
p[66,73]<-1
p[67,84]<-1
p[67,73]<-1
p[68,74]<-1
p[68,75]<-1
p[69,76]<-1
p[70,76]<-1
p[71,79]<-1
p[72,80]<-1
p[73,83]<-1
p[74,83]<-1
p[75,77]<-1
p[75,78]<-1
p[76,78]<-1
p[77,90]<-1
p[78,82]<-1
p[79,82]<-1
p[79,91]<-1
p[80,81]<-1
p[80,98]<-1
p[81,82]<-1
p[81,91]<-1
p[82,90]<-1
p[83,86]<-1
p[84,87]<-1
p[84,85]<-1
p[85,86]<-1
p[86,89]<-1
p[87,88]<-1
p[88,95]<-1
p[89,95]<-1
p[90,92]<-1
p[90,93]<-1
p[91,94]<-1
p[92,96]<-1
p[93,97]<-1
p[94,97]<-1
p[95,100]<-1
p[96,100]<-1
p[97,100]<-1
p[98,100]<-1
p[99,100]<-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,10,3)

time<-862.619