多维不确定环境下的生物能源供应链网络优化设计

发布时间：2018-05-06 10:25

本文选题：生物能源 + 供应链设计　；参考：《东北大学》2014年硕士论文

【摘要】：世界化石能源的日渐枯竭令能源紧张问题愈发严重。生物能源作为一种可再生能源,其开发和利用在世界各国逐步兴起并飞速发展,尤其是以玉米秸秆等非粮食作物为原料的第二代生物能源的生产,因其原料的来源广泛、成本低廉等优势而备受关注。那么如何实现生物能源的持续稳定供应则成为亟待解决的问题,这就促使生物能源供应链的网络优化设计成为了供应链研究领域的一个新的研究热点。然而,现实生产运营中存在着大量的不确定性,给生物能源供应链的优化设计带来了巨大的挑战。更重要的是,不确定性事件的发生会对生物能源的生产产生巨大的负面影响。因此,进行多维不确定性环境下的生物能源供应链网络优化设计意义重大。随着环境问题日益严峻,环境效益不容忽视,以往只重经济效益的运营模式已不可行,企业需要“两手抓,两手都要硬”,因此,生物能源供应链中的二氧化碳排放等环境问题,也成为另外一个值得探讨的研究方向。与此同时,传统供应链的相关研究将决策者假设为完全理性,而在现实中,面对同样不确定性的不同决策者,由于具有不同的风险偏好,最终会做出不同的决策,所以在为决策者提供决策参考时考虑其行为偏好是十分必要的。而目前学者对于生物能源供应链网络设计问题的研究,常常存在简化不确定性、忽视环境效益以及对决策者行为考虑的欠缺,因此很有必要在前人研究的基础上添加缺失因素,丰富该领域的研究。本文以生物能源供应链为研究对象,主要研究了多维不确定性环境下的生物能源供应链网络优化设计问题,并引入环境效益和风险偏好概念,分别构建了考虑环境效益和决策者行为的数学模型,其中不确定性包括生物质原料供应量和采购价格的不确定性以及生物能源需求的不确定性,环境效益通过二氧化碳排放成本进行衡量,风险偏好由累积风险曲线表达,最终建立相应的线性混合整数随机规划模型,通过对基于辽宁省相关数据的算例进行求解,得到了生物能源供应链网络结构和相关运营决策,如生物能源精炼厂的选址、产能和产量、网络中各节点的配送关系和配送量、二氧化碳的排放成本等,并为不同风险偏好的决策者提供相应的网络设计方案。最后,通过对模型中关键参数进行灵敏度分析,进一步验证了模型的有效性,从而证明了本文所建立的模型可以为决策者提供有效的决策支持。
[Abstract]:The depletion of fossil energy in the world makes the problem of energy tension more and more serious. As a kind of renewable energy, the development and utilization of bioenergy is rising and developing rapidly all over the world, especially the production of the second generation bioenergy, which takes corn straw and other non-food crops as raw materials, because of its wide sources of raw materials. Low cost and other advantages have attracted much attention. Therefore, how to realize the sustainable and stable supply of bioenergy becomes an urgent problem, which makes the network optimization design of bioenergy supply chain become a new research hotspot in the field of supply chain research. However, there are a lot of uncertainties in the production and operation, which brings great challenges to the optimization design of bioenergy supply chain. More importantly, the occurrence of uncertain events will have a huge negative impact on bioenergy production. Therefore, it is of great significance to optimize the design of bioenergy supply chain network under the environment of multidimensional uncertainty. With the increasingly serious environmental problems, environmental benefits can not be ignored. In the past, only economic benefits of the operation model is no longer feasible, enterprises need to "two hands, both hands must be hard", therefore, Environmental issues such as carbon dioxide emissions in bioenergy supply chains have also become another research direction worthy of discussion. At the same time, the traditional supply chain studies assume that the decision-makers are completely rational. In reality, different decision makers with the same uncertainty will make different decisions because of their different risk preferences. Therefore, it is necessary to consider the behavior preference of decision-makers when providing decision-making reference. However, the current research on bioenergy supply chain network design often has the lack of simplification uncertainty, neglect of environmental benefits and consideration of decision makers' behavior. Therefore, it is necessary to add missing factors to previous studies. Enrich the research in this field. In this paper, the bioenergy supply chain is taken as the research object. The optimization design of bioenergy supply chain network under multi-dimensional uncertainty is studied, and the concepts of environmental benefit and risk preference are introduced. Mathematical models considering environmental benefits and decision makers' behaviors are constructed respectively. The uncertainties include the uncertainty of biomass feedstock supply and purchase price and the uncertainty of bioenergy demand. Environmental benefits are measured by the cost of carbon dioxide emissions, and risk preference is expressed by cumulative risk curve. Finally, a linear mixed integer stochastic programming model is established and solved by an example based on relevant data of Liaoning Province. The network structure of bioenergy supply chain and related operational decisions are obtained, such as the location of bioenergy refineries, capacity and output, the distribution relationship and quantity of nodes in the network, the cost of carbon dioxide emissions, etc. And provides the corresponding network design scheme for different risk preference decision makers. Finally, the sensitivity analysis of the key parameters in the model is carried out to further verify the validity of the model, which proves that the proposed model can provide effective decision support for decision makers.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.2;F274

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