There are a variety of measures of evenness of the sums (group-values). For example, one alternative is to try to minimize the difference between the biggest and smallest sum.
Minimizing the standard deviation is the same as minimizing the variance.
However, the mean of the sums is fixed, so minimizing the variance is the same as minimizing the sum of squares of the group-values.
This is getting a bit closer to a 'standard' optimization problem.
It's somewhat related to the Job-shop scheduling problem and a number of other problems.
There are various job-scheduling programs, some of which might be able to work on your problem, but they usually tend to focus on minimizing the maximum completion time (that would correspond to minimizing the largest set, which may not give you a good solution).
From a quick glance it looks like the
partitions package in R can generate partitions for you - but unfortunately the number of possible partitions is going to be huge in your case, so you may have to settle for some approximate algorithm (in a similar fashion to some of the bin-packing problems, for example). [Approximate algorithms can often generate very good solutions.]
There may be some value in this:
but it does seem to look mostly at bidding-solutions.
If you have a mixed problem (that is, one which includes divisible assets like cash), your job should be easier.
There might be something to be said for starting with some reasonable solution and using say tabu-search or simulated annealing or something to try to improve it.
If this is a one-off problem can you post the some numbers proportional to the values (it won't affect anything to multiply them by some arbitrary constant like 1.375) - it might help to have something concrete to think about.