Question

I need to solve the following problem:

I have an alphabet of n symbols and a dictionary with N words of m 
symbols (n in the order of tens, N in the order of tens of thousands, m 
=3D 4, say)

Assuming each symbol has a definite probability, I need to generate a 
list of M words (M in the order of 100) taken from the dictionary in 
which the proportion of each symbol matches as best as possible the 
required probability.

Is this a problem that can be solved using GLPK?

Thanks.

Bes regards,

Federico Miyara

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