I do the following problem to solve and was wondering if this can be easily done using preferably R:

+ I have a set of, let's say, 10 variables: n(varibale) = 10

e.g. var <- c(a,b,c,d,e,f,g,h,i,j)

+ per experiment, I want to pick 4 variables

e.g. exp1 <- c(a,b,c,d), exp2 <- c(e,f,g,h), ...

+ each variable should be present in 4 different experiments

+ each varibale may co-occur in max. 2 experiments with another variable

Questions:

1) What is the number of minimal experiments that all of the above prerequisites are met?

2) Report a list of the combinations

It would be great to have a script that is flexible for all prerequisites (R, pearl, linux,...).

Thanks a lot already in advance!

Naina

## modified minimal set cover problem

### Re: modified minimal set cover problem

Yes, thanks a lot!

But this was only an example. Later I will have much larger numbers that I cannot do it by hand anymore.

However, I found an R-package that provides at least part of the solution (http://www.r-bloggers.com/generating-ba ... igns-bibd/)

But this was only an example. Later I will have much larger numbers that I cannot do it by hand anymore.

However, I found an R-package that provides at least part of the solution (http://www.r-bloggers.com/generating-ba ... igns-bibd/)