A hybrid decomposition algorithm for designing a multi-modal transportation network under biomass supply uncertainty

• Proposed two-stage stochastic programming model for biomass co-firing supply chain.
• Scenario generated using prediction errors from historical and forecasted supply.
• A hybrid decomposition algorithm connecting SAA with an enhanced PHA is proposed.
• Case study reveals the impact of feedstock uncertainty on co-firing supply chain.

This study presents a two-stage stochastic programming model for the design and management of a biomass co-firing supply chain network under feedstock supply uncertainty. To represent a more realistic case, we generate scenarios from prediction errors of the historical and forecasted biomass supply availabilities. We solve the model using a hybrid decomposition algorithm that combines Sample average approximation with an enhanced Progressive hedging algorithm. The proposed algorithm is validated via a real-world case study using data from Mississippi and Alabama. Computational results indicate that the proposed algorithm is capable of producing high quality solutions in a reasonable amount of time.