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

TL;DR

This paper presents an approximate optimization method for long-horizon tank blending and scheduling in chemical plants, combining MIQCP modeling, discretization, and a rolling horizon approach for efficient planning.

Contribution

It introduces a novel discretization-based approximation of a nonconvex MIQCP model, enabling faster scheduling in complex chemical plant operations.

Findings

Supports fast planning cycles in chemical plant scheduling

Effective handling of long horizons and multiple suppliers

Validated with industry-representative data sets

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.