复杂风险环境下弹性生物燃料供应链网络集成优化方法研究

发布时间：2018-04-12 16:24

本文选题：生物燃料 + 弹性供应链　；参考：《东北大学》2013年硕士论文

【摘要】：在全球能源危机的背景下,生物燃料的发展与应用受到越来越多的关注,为了保证生物燃料能够持续有效的供应,一个有效、稳定的生物燃料供应链网络是必不可少的,因此,对于生物燃料供应链网络优化问题的研究成为一个新的研究热点。目前,该领域已有文献大多侧重于对确定性环境下的生物燃料供应链网络优化问题进行研究,有少数学者在研究中考虑了不确定性因素的影响,但仅局限于供应量、需求量以及价格的不确定性,并未考虑失效风险可能对生物燃料供应链造成的危害,也未曾考虑通过嵌入弹性策略的方式增强生物燃料供应链网络应对多种不确定因素和失效风险的能力。然而,在现实的生物燃料供应链网络中,诸如地震、洪水、飓风等可能引发设施或供应失效的事件时有发生,此类失效事件虽然发生概率较小,可一旦发生,其造成的损失却极其巨大。因此,为了构建稳定、有效的弹性生物燃料供应链网络,必须对包括多种不确定性因素和失效事件的复杂风险环境影响进行充分考虑,同时,使用有效的弹性策略增强生物燃料供应链网络对复杂风险环境的适应能力。本文主要研究了复杂风险环境下的生物燃料供应链网络优化问题,在综合考虑多种不确定性因素与失效风险的前提下,进行生物燃料供应链网络的结构与运作集成优化,其中,复杂风险环境主要包括生物质原料的供应量、最终产品需求量及价格波动、原料产地与精炼设施可能发生的失效等,并使用随机情境生成技术,对以上因素进行了表达,同时,考虑使用多源采购、替代源供应和常规库存等弹性策略来增强生物燃料供应链网络的弹性,在此基础上构建相应的多周期线性混合整数随机规划模型,通过模型求解,帮助生物燃料供应链网络进行结构与运作相关决策,其中集成了以下决策问题：(1)各节点对上游供应商的选择,(2)网络中物流量分配相关问题的确定,(3)生物乙醇精炼厂的选址,(4)生产规模与数量的确定以及对于各种弹性策略的选择。文中研究了两种不同类型的生物燃料供应链网络模型,并从系统收益最大化和效率与弹性的权衡两个角度进行了供应链网络结构与运作集成优化方法研究。最后,均通过对数值算例进行求解,验证了优化模型的有效性,并对优化结果进行了灵敏度分析,考察了模型中的关键参数对于模型优化结果的影响,从而为决策者进行生物燃料供应链网络优化决策提供必要的参考。
[Abstract]:In the context of the global energy crisis, the development and application of biofuels has received more and more attention. In order to ensure the sustainable and efficient supply of biofuels, an effective and stable supply chain network of biofuels is essential.The optimization of biofuel supply chain network has become a new research hotspot.At present, most of the literatures in this field focus on the optimization of biofuel supply chain network in the deterministic environment. A few scholars have considered the influence of uncertainty in the research, but only in the supply.Uncertainty about demand and price does not take into account the potential harm of failure risks to biofuel supply chains,It is also not considered to enhance the capacity of biofuel supply chain networks to deal with multiple uncertainties and failure risks by embedding elastic strategies.However, in a realistic biofuel supply chain network, events such as earthquakes, floods, hurricanes that may cause facility or supply failures occur from time to time, although they are less likely to occur once they occur.The damage is enormous.Therefore, in order to build a stable and effective flexible biofuel supply chain network, it is necessary to take full account of the complex risk environmental impacts, including a variety of uncertainties and failure events, and at the same time,Effective elastic strategies are used to enhance the adaptability of biofuel supply chain networks to complex risk environments.This paper mainly studies the optimization of biofuel supply chain network under complex risk environment. Under the premise of synthetically considering many uncertain factors and failure risks, the structure and operation of biofuel supply chain network are optimized.The complex risk environment mainly includes the biomass raw material supply, the final product demand and the price fluctuation, the raw material origin and the refining facility may have the invalidation and so on, and uses the random situation generation technology, has carried on the expression to the above factors, at the same time,In order to enhance the elasticity of biofuel supply chain network, a multi-period linear mixed integer stochastic programming model is constructed based on the elastic strategies of multi-source purchasing, alternative source supply and conventional inventory, and solved by the model.To help biofuels supply chain networks make structural and operational decisions,This paper integrates the following decision problem: 1) the selection of upstream suppliers by each node and the determination of the problems related to the distribution of material flow in the network. (3) the location of the bio-ethanol refinery is 4)) the scale and quantity of production and the choice of various elastic strategies.In this paper, two different types of biofuel supply chain network models are studied, and the optimization methods of supply chain network structure and operation integration are studied from the perspectives of maximum system income and trade-off between efficiency and elasticity.Finally, the effectiveness of the optimization model is verified by solving numerical examples, and the sensitivity of the optimization results is analyzed, and the influence of the key parameters in the model on the optimization results is investigated.Therefore, it provides the necessary reference for decision makers to optimize the biofuel supply chain network.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F426.2;F274

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