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
= 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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