An Approximate Method for the Optimization of Long-Horizon Tank Blending and Scheduling Operations

Abstract

We address a challenging tank blending and scheduling problem regarding operations for a chemical plant. We model the problem as a nonconvex MIQCP, then approximate this model as a 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.