An approximate method for the optimization of long-Horizon tank blending and scheduling operations

We address a challenging tank blending and scheduling problem that arises in the specialty chemical industry. We model the problem as a nonconvex mixed-integer quadratically-constrainted programm (MIQCP) and then approximate this model as a mixed-integer linear program (MILP) using a discretization-based approach. We combine a rolling horizon approach with the discretization of individual chemical property specifications to deal with long scheduling horizons, time-varying quality specifications, and multiple suppliers with discrete arrival times. This approach has been evaluated using industry-representative data sets from the specialty chemical industry. We demonstrate that the proposed approach supports fast planning cycles. Published by Elsevier Ltd.