A two-stage stochastic programming model for the optimal planning of a coal-to-liquids supply chain under demand uncertainty.

With the growing global energy demand and worsening ecological environment, coal-abundant countries are actively developing the technologies which could convert coal to liquid fuels, so called coal-to-liquids (CTL), to adjust and optimize energy structure, guarantee energy security, and reduce environmental pollution. For the optimal planning of a CTL supply chain, a two-stage stochastic programming model is established to maximize the profit of the CTL supply chain under the products demand uncertainty. Various technical and operational constraints involving the infrastructure construction, CTL plants production, products and coal transport as well as the influence of products oversupply, are considered in the model. Based on the sample average approximation method, a number of finite scenarios for the uncertain parameters are generated, the established stochastic model is converted into an equivalent deterministic model and then solved. Finally, the model was successfully applied to a real-world CTL supply chain in Sinkiang, China. The applicability of the proposed model was testified. Also, comparative studies were carried out to illustrate the influence of the uncertainty on the CTL supply chain. [ABSTRACT FROM AUTHOR]