Reformation of the multiperiod MILP model for capacity expansion of chemical process

Abstract: "The problem of selecting processes and capacity expansion policies for a chemical complex consisting of continuous processes can be formulated as a multiperiod mixed integer linear programming problem. Based on a variable disaggregation technique that exploits lot sizing substructures, we propose two reformulations of the conventional MILP model. The first one is an NLP reformulation that yields very quickly good suboptimal solutions. The second is an MILP reformulation for exact solutions that leads up to an order of magnitude faster computational results for large problems due to its tighter linear programming relaxation."