This has only the most tenuous connection to bioinformatics if I make a number of assumptions about why you're trying to do this. You should really post this on an R forum. Having said that:

m <- matrix(c(20,25,100,126,30,35,190,226,25,20,126,100,35,30,226,190), ncol=4)
overlap <- apply(m, 1, function(x) length(intersect(x[1]:x[2], x[3]:x[4])))
cbind(m, overlap)

This should work:

# dummy data
df <- read.table(text="start1  end1    start2  end2    
20     30      25      35
25     35      20      30    
100     190    126      226      
126     226    100      190",header=TRUE)

# Count overlap
df$bp_overlapped <- 
  sapply(1:nrow(df), function(x)
  {
    length(
      intersect(c(df[x,1]:df[x,2]),
                c(df[x,3]:df[x,4])))
  })

You can use findOverlaps command in R. The script is as follows:

data2=read.table("C:/file_name.txt",sep = "\t",fill = TRUE)
data2=data2[data2[,1]=="Chromosome_name",]
end=0
start=data2[,2]

for(i in 1:length(data2[,1]))
{
  x=length(data2[i,])-sum(is.na(data2[i,]))
  end[i]=data2[i,x]
}
chr=data2[,1]
genes=data.frame( chr,start,end)

library(IRanges)
query <- IRanges(start,end)

result=read.table("C:/GC/chromosome_name.txt/result.txt")

subject <- IRanges(c(result$start1), c(result$end1))
tree <- IntervalTree(subject)
findOverlaps(query, tree, select = "all")