Work

Integration of MILP and Discrete-Event Simulation for Flowshop Scheduling Using Benders Decomposition

Year: 2025

Type: conference-paper

Abstract: Real-world flowshop problems which are very common in the chemical industry are often difficult to solve in a reasonable time with allocation, sequencing, and lot-sizing decisions. Although great progress has been made in the last 20 years regarding MILP model formulations and solution algorithms, realistically-sized flowshop problems with resource and buffer constraints are still difficult to solve. On the other hand, discrete-event simulation (DES) allows for very detailed modelling of process plants, but lacking of optimization capabilities. Simulation Optimization (SO) combines the high-detail DES with mathematical optimization. We show that is possible to integrate MILP and DES using Benders decomposition. We explain the Benders-DES (BDES) approach with a small motivation example with makespan minimization objective and apply it to a real-world case study of a formulation plant with seven formulation and filling lines with sequencing, allocation, and lot-sizing decisions. We show that the BDES approach performs comparably to the original monolithic-sequential MILP-DES approach. However, the key advantage of this method is the ability to leverage MILP optimization power without requiring a detailed model description.

Source: Systems and Control Transactions

DOI: 10.69997/sct.180841

Authors: Roderich Wallrath, Edwin Zondervan, Meik B. Franke

Institutions: Bayer (Germany), University of Twente

Language: English

Topic: Scheduling and Optimization Algorithms

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: Bayer