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本文研究了一个包含供应点、中转点和需求点的三级可靠供应链网络设计问题(RSCNDP).文章同时考虑了供应端的不确定性(节点中断的可能性)和需求端的不确定性(需求量的波动性),针对这些因素,采用情景的方法描述,并结合p-鲁棒模型的优点提出了一个新的混合整数规划模型.在模型中,α,β两参数分别表示决策者对节点中断和需求波动的风险偏好,优化的目标是在给定的风险偏好下最小化设施的固定成本和产品的运输成本.文章提出了一个由最短增广链法和遗传算法的相结合的混合智能算法来求解该模型,并结合实际进行了相应的数值分析.结论显示决策者的风险偏好对可靠供应链网络的设计会产生重大的影响,而在面临风险时,可靠的供应链网络表现要优于确定型的供应链网络,这些为企业的供应链管理决策提供了理论支撑.
This paper studies a three-level reliable supply chain network design problem (RSCNDP) with supply, transit and demand points.The article considers both supply-side uncertainty (the probability of node disruption) and demand-side uncertainty (demand In this model, the α and β parameters respectively represent the difference between the decision-maker’s contribution to the node Interruption and demand volatility, the objective of optimization is to minimize the fixed costs of facilities and the transportation cost of products under a given risk preference.This paper presents a hybrid intelligence consisting of shortest augmented chain method and genetic algorithm Algorithm to solve the model and make corresponding numerical analysis according to the actual situation.The conclusion shows that the risk preference of decision-maker has a significant impact on the design of reliable supply chain network, while the reliable supply chain network performance is superior in the face of risk For the deterministic supply chain network, these provide theoretical support for the enterprise’s supply chain management decision-making.