SIMPRONET (Stochastic Inventory Management for Process Networks) is a program that addresses medium term planning of chemical complexes with integration of stochastic inventory management under supply and demand uncertainty. Formulated as a mixed-integer nonlinear program (MINLP) with a nonconvex objective function and nonconvex constraints.
Given a process network consisting of a set of dedicated processes with fixed production capacity, a unit production cost and production time;
and a set of chemicals (feedstocks, intermediates or final products, and each of them can be purchased from the suppliers, produced in the chemical complex and sold to the markets.), the model determines the optimal purchases of the feedstocks, production levels of the processes, sales of final products and safety stock levels of all the chemicals in order to minimize the total purchase, production and inventory cost.
SIMPRONET is based on the paper Stochastic Inventory Management for Tactical Process Planning under Uncertainties: MINLP Models and Algorithms by F. You and I. Grossmann (2009); and has been developed by Rosanna Franco under the supervision of Ignacio E. Grossmann.