期刊
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
卷 22, 期 1, 页码 119-151出版社
SPRINGER
DOI: 10.1007/s10098-019-01773-2
关键词
Bioethanol supply chain; Lignocellulosic biomass; Resiliency; Disruption; Robust possibilistic programming; Stochastic programming
In this work, we propose a mixed-integer linear programming model to address the design and planning of a multi-feedstock lignocellulosic bioethanol supply chain network. In order to provide resiliency against existing epistemic uncertainties and disruption risks in the supply chain, a hybrid robust stochastic-possibilistic programming approach is employed. The proposed model minimizes total expected cost of the supply chain over non-disruption and disruption scenarios while limiting greenhouse gas emissions for sustainability considerations. The model determines the optimal supply chain strategic and tactical decision variables such as location, capacity and technology of biorefineries, transportation modes, shipments, inventory levels and production and import amounts. The performance of the model is evaluated through a real case study developed in Iran. Comparing the proposed resilient model with its non-resilient counterpart reveals that the proposed model is superior both in cost and GHG emissions reductions. Graphic abstract
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据