  This paper describes an approximate method for global optimization of
polynomial programming problems with bounded variables. The method uses a
reformulation and linearization technique to transform the original polynomial
optimization problem into a pair of mixed binary-linear programs. The solutions
to these two integer-linear reformulations provide upper and lower bounds on
the global solution to the original polynomial program. The tightness of these
bounds, the error in approximating each polynomial expression, and the number
of constraints that must be added in the process of reformulation all depend on
the error tolerance specified by the user for each variable in the original
polynomial program. As these error tolerances approach zero the size of the
reformulated programs increases and the calculated interval bounds converge to
the true global solution.
