A hybrid decomposition algorithm for designing a multi-modal transportation network under biomass supply uncertainty. (October 2016)

• Record Type: Journal Article
• Authors: Poudel, Sushil Raj; Marufuzzaman, Mohammad; Bian, Linkan
• Is Part Of: Transportation research. Volume 94(2016)
• Page Start: 1
• Page End: 25
• Publication Date: 2016-10
• Subjects: Coal supply chain network -- Multi-modal facilities -- Sample average approximation -- Progressive hedging algorithm -- Rolling horizon heuristics; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2016.07.004
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: 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. Abstract: 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.