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Biofeedstock Supply Chain Logistics Dynamic Modeling: Eastern Redcedar

Craige, Collin
A body of knowledge exists for the Eastern Redcedar supply chain; however, the available data is not sufficient to fully evaluate the numerous potential commercialization strategies. The ability to model a supply chain in its entirety, from identifying the facility location and feedstock availability through the harvest, transport, processing, and refining stages is a critical component of characterizing the feasibility of a given strategy. To facilitate the development of Eastern Redcedar commerce, a comprehensive, modular, commodity based supply chain model was developed as a computational tool for decision makers who are considering investing capital in developing or expanding Easter Redcedar markets. This model is web based, to provide improved accessibility and ease of use while its modular structure gives it the flexibility to evaluate niche markets. Geospatial programming is used to perform location allocation, develop service areas, routes, and biomass yield maps. This data, combined with user inputs, is used to approximate costs at each stage in the supply chain. Rejection sampling is used to generate random numbers according to empirical probability distribution functions for key cost variables in Monte Carlo simulations. The interdependency, cost impact and sensitivity of variables on total system cost are derived from one-way sensitivity analyses. All results are displayed as interactive bar graphs, line charts, and maps. The model is expected to reduce the risk associated with the production of Eastern Redcedar products and provide a strong foundation for expanding the model to include other biomass feedstocks and end products.