Research On Integrated Optimization Approach Of Resilient Biofuel Supply Chain Network Under Complex Risk Environment

Under the background of global energy crisis, people are paying more and more attention to the development and application of biofuel. In order to ensure a sustainable and effective biofuel supply, an effective and stable biofuel supply chain network is essential, therefore, researches on biofuel supply chain network optimization has become a new research hotspot, however, most of the researches on biofuel supply chain network currently are mainly focused on deterministic problems, only a few study has considered the influence of uncertainty factors, but the factoers are limited to supply, demand and price uncertainties, more extreme uncertainty events such as disruption has not been taken into account, while the extreme uncertainty factors may cause most serious damage to biofuel supply chain, there is also no research that has considered of embedding resilience strategy into biofuel supply chain network so that to create the ability to cope with uncertainties. In reality, however, disruptions such as earthquake, flood, hurricane etc. may result in facilities or supply disruption, probability of such disruption event is small, but once happened, the damage is extremely huge. Therefore, to build a stable and effective resilient biofuel supply chain network, the influence of copmplex risk environment needs sufficient consideration, at the same time, effective strategy to enhance resilience of biofuel supply chain network under uncertain environment should also be used.In this paper, the optimization problem of biofuel supply chain network under copmplex risk environment is studied with comprehensive consideration of various uncertain and disruption risks including biomass raw material supply and price fluctuations, final product demand, possibility of raw material supply and refining facilities disruption, by using stochastic scenario generation technique, the factors in the above are expressed appropriately, at the same time, resilient strategy such as multi-sourcing, inventory and alternative source of supply are embeded to enhance the flexibility of biofuel supply chain network. A multi-cycle mixed integer linear stochastic programming model is build to make biofuels supply chain network structure and operation related decisions which include the allocation of suppliers, the through put in the network, the location, production scale and number of bioethanol refineries and the choices of various resilient strategies.In this paper, two different types of biofuel supply chain network models were studied under profit maximization and efficiency-resilience trade-off respectively, effectiveness of both models have been proved by numerical examples, sensitivity analysis has been carried out by verifying some of the key parameters in the optimization models so that to provide management insights for decision makers in biofuel supply chain network optimization.