Olga Walz | Searcharxiv

arXiv2026

Mixed-integer programming formulations for optimal reconfiguration of supply chains

Supply chains are interconnected networks of processes and operations producing and delivering high-value products. These chains are increasingly subjected to structural changes from the energy transition and other external factors. To address this, this work develops mixed-integer programming formulations to identify optimal reconfigurations that preserve industrial operations and profitability. We propose products and spatial neighborhoods to restrict the feasible search space and enable fast heuristic solutions. Furthermore, this restriction combines structural and product-based information, thus allowing to explore and define multiple reconfiguration scenarios. We demonstrate the approach using an agricultural waste case study, showing its ability to quickly produce good quality solutions.

math.OC↗

arXiv2025

CarAT: Carbon Atom Tracing across Industrial Chemical Value Chains via Chemistry Language Models

The chemical industry is increasingly prioritising sustainability, with a focus on reducing carbon footprints to achieve net zero. By 2026, the Together for Sustainability (TfS) consortium will require reporting of biogenic carbon content (BCC) in chemical products, posing a challenge as BCC depends on feedstocks, value chain configuration, and process-specific variables. While carbon-14 isotope analysis can measure BCC, it is impractical for continuous industrial monitoring. This work presents CarAT (Carbon Atom Tracker), an automated methodology for calculating BCC across industrial value chains, enabling dynamic and accurate sustainability reporting. The approach leverages existing Enterprise Resource Planning data in three stages: (1) preparing value chain data, (2) performing atom mapping in chemical reactions using chemistry language models, and (3) applying a linear program to calculate BCC given known inlet compositions. The methodology is validated on a 27-node industrial toluene diisocyanate value chain. Three scenarios are analysed: a base case with fossil feedstocks, a case incorporating a renewable feedstock, and a butanediol value chain with a recycle stream. Results are visualised with Sankey diagrams showing the flow of carbon attributes across the value chain. The key contribution is a scalable, automated method for real-time BCC calculation under changing industrial conditions. CarAT supports compliance with upcoming reporting mandates and advances carbon neutrality goals by enabling systematic fossil-to-biogenic substitution. Through transparent, auditable tracking of carbon sources in production networks, it empowers data-driven decisions to accelerate the transition to sustainable manufacturing.

cs.CE↗