  In this technical report, a new formulation for embedding a neural network
into an optimization model is described. This formulation does not require
binary variables to properly compute the output of the neural network for
specific types of problems. Preliminary experiments show that this
reformulation resulted in faster computation times when solving a proposed
showcase model, in which non-linearity is necessary to be computed. This is in
comparison with the classic formulation and off-the-shelf tools of commercial
solvers.
