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One of the biggest challenges in solving optimization engineering problems is rooted in the nonlinearities and nonconvexities, which arise from bilinear terms corresponding to component material balances and/or concave functions used to estimate capital cost of equipments. The procedure proposed uses an MILP lower bound constructed using partitioning of certain variables, similar to the one used by...
We propose a new method to obtain the global optimum of MINLP problems containing bilinearities. Our special method that contracts the bounds of one variable at a time allows reducing the gap between a linear lower bound and an upper bound obtained solving the original problem. Unlike some methods based on variable partitioning, our bound contraction procedure does not introduce new integers or intervals...
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