Multiperiod capacity expansion for optimal design of industrial complexes

The problem of selecting processes and capacity expansion policies for a chemical complex consisting of continuous chemical processes can be formulated as a multiperiod mixed integer linear programming problem (MILP). Based on a variable disaggregation technique which exploits lot sizing substructures, The authors propose a nonstandard reformulation of the conventional MILP model. The new formulation leads to up to an order of magnitude faster computational results for large problems due to its tighter linear programming relaxation.