  In this paper, we propose an optimization-based mechanism to explain power
law distributions, where the function that the optimization process is seeking
to optimize is derived mathematically, then the behavior and interpretation of
this function are analyzed. The derived function shows some similarity to the
entropy function in representing order and randomness; however, it also
represents the energy, where the optimization process is seeking to maximize
the number of elements at the tail of the distribution constrained by the total
amount of the energy. The results show a matching between the output of the
optimization process and the power law distribution.
