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A hybrid decomposition algorithm for designing a multi-modal transportation network under biomass supply uncertainty |
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| Affiliation: | 1. Ecole des Mines de Saint-Etienne, Department of Manufacturing Sciences and Logistics, CMP, CNRS UMR 6158 LIMOS, 880 avenue de Mimet, 13541 Gardanne, France;2. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran;3. Beedie School of Business, Simon Fraser University, Vancouver, Canada;1. Department of Mechanical and Industrial Engineering, Concordia University, Montreal, Canada;2. Interuniversity Research Centre on Enterprise Networks, Logistics, and Transportation (CIRRELT), Montreal, Canada;3. Department of Mechanical Engineering, Université Laval, Quebec, Canada;1. Department of Engineering Science, The University of Auckland, 70 Symonds Street, Auckland 1001, New Zealand;2. Department of Management Science, Lancaster University, Bailrigg, Lancaster LA1 4YX, United Kingdom |
| 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. |
| Keywords: | Coal supply chain network Multi-modal facilities Sample average approximation Progressive hedging algorithm Rolling horizon heuristics |
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