Vol. 3, No. 3 (Summer 2016) 1-10   

Link: http://www.jree.ir/Vol3/No3/1.pdf
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  A Switchgrass-based Bioethanol Supply Chain Network Design Model under Auto-Regressive Moving Average Demand
H. Ghaderi, M. Asadi and S. Shavalpour
( Received: October 24, 2015 – Accepted: August 24, 2016 )

Abstract    Switchgrass is known as one of the best second generation lignocellulosic feedstock for bioethanol production. Designing an efficient switchgrass-based bioethanol supply chain (SBSC) is an essential requirement for commercialization of bioethanol production. This paper presents a mixed integer linear programming (MILP) model to design SBSC in which the bioethanol demand is under ARMA time series models. It is studied how ARMA time series structure of bioethanol demand affect the supply chain design. A case study based on North Dakota state in the United States demonstrates application of the proposed model to design the most optimal SBSC.in addition, to provide insights for efficiently designing the SBSC, the ARMA models of bioethanol demand is used to forecast SBSC design for the period 2013 to 2020.


Keywords    ARMA, switchgrass, bioethanol supply chain, network design, mixed integer programming.


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