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Development of an integrated tactical and operational planning model for supply of feedstock to a commercial‐scale bioethanol plant
19
Citations
20
References
2013
Year
Supply Chain OptimizationEngineeringBioenergyLogistics OptimizationAgricultural EconomicsBiomass Supply ChainClosed-loop Supply ChainOptimal System DesignLogisticsSupply ChainSystems EngineeringOptimization ModelLogistics ModelBiomass UtilizationManufacturing PlanningSupply Chain DesignSupply Chain ManagementProduction PlanningCircular BioeconomyBiomanufacturingOperational Planning ModelCommercial‐scale Bioethanol PlantEnergy ManagementBiomass ResourceBusinessSupply Chain Analysis
Abstract In this paper, a new modeling approach is proposed to integrate the tactical and operational planning levels in the biomass supply chain. The proposed approach includes an optimization model and a simulation model. The integration is made between these models (i) to assure the fulfillment of the daily biomass demand year‐round for a commercial‐scale cellulosic ethanol plant and (ii) to reduce biomass delivery costs. The optimization model prescribes the design of the supply area in a way that the annual biomass demand is met at a minimum delivery cost for a five‐year planning horizon. Given the design of the supply area, the simulation model schedules the flow of multi‐biomass in the supply chain to meet the daily biomass demand of the ethanol plant subject to the dynamics and uncertainties in the supply chain. If the daily demand cannot be met, the outputs of the simulation model are used to adjust the design in the optimization model to assure the fulfillment of the daily demand. The application of the integrated model to a proposed commercial‐sized bioethanol plant shows the efficiency of the integrated approach to design the supply area in a way that the daily biomass demand is met at the minimum delivery cost possible. The results of the sensitivity analysis reveal that the most influential parameter on the design is biomass yield. In addition, bale bulk density, in‐farm and road transportation operations, and farmer participation rates have the highest impact on delivery cost compared to other input parameters. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd
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