Automated targeting for green supply chain planning considering inventory storage losses, production and set-up time

Aggregate planning has been used to maximize profit of a supply chain over a specified time horizon while satisfying customers’ demand. However, previous work on aggregate planning did not consider factors such as inventory sizing, inventory losses, production, and setup time simultaneously. These factors are imperative as they influence a decision-maker’s capability to ascertain the true performance of a given supply chain. This research gap is addressed in this work by developing an improved aggregate planning model to optimize inventory allocation in green production supply chains based on inventory storage size, storage losses, production, and set-up time. To demonstrate the applicability of the model, a biochar production supply chain case study was solved. Results from the case study confirm that optimal production and inventory allocation are dependent on storage losses and unit storage costs. These results were compared to those obtained via a published method. The comparison indicated that the presented method yielded more realistic results.