Strategic redesign of the forest-based biomass supply chain through optimization and sensitivity analysis
The Forest Biorefinery Supply Chain (FBSC) redesign problem is addressed. A Generalized Disjunctive Programming (GDP) model is constructed and it is reformulated as Mixed Integer Linear Programming (MILP). The proposed superstructure of FBSC scope (i) the strategic location of forest biomassbased bi...
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| Autores principales: | , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/151835 https://publicaciones.sadio.org.ar/index.php/JAIIO/article/download/348/289 |
| Aporte de: |
| Sumario: | The Forest Biorefinery Supply Chain (FBSC) redesign problem is addressed. A Generalized Disjunctive Programming (GDP) model is constructed and it is reformulated as Mixed Integer Linear Programming (MILP). The proposed superstructure of FBSC scope (i) the strategic location of forest biomassbased biofuel facilities, and its integration with installed traditional forest industries.In addition, the model determine (ii) feedstock harvesting amount at each forest area; and (iii) transportation flows along all FBSC arcs over a multi-period horizon planning. The applicability of the proposed model is demonstrated through a case study considering different uncertainty settings. A series of sensitivity analyses is performed to determine the impact of variations on the proposedFBSC. The variations in the selling price of products, biomass availability, and demand of products are addressed in the sensitivity analysis. |
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