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出 处:《系统工程理论与实践》2015年第8期2025-2033,共9页Systems Engineering-Theory & Practice
基 金:国家自然科学基金(71071113);高等学校博士学科点专项科研基金(20100072110011);上海市哲学社会科学规划课题(2010BZH003);中央高校基本科研业务费专项资金
摘 要: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 reliable supply chain network design problem (RSCNDP) including sup- ply, transshipment and demand. The provider-side uncertainty (facility disruption) and the receiver-side uncertainty (demand uncertainty) are both considered, and scenario method is used to describe these un- certainties. Based on the p-robust model, a mixed-integer programming (MIP) model is proposed, where two parameters are used to describe the risk preferences of decision makers towards facility disruption and demand uncertainty. The objective function is to minimize the sum of facility fixed cost and transportation cost under a given pair of risk preference values. We develop a hybrid meta-heuristic algorithm based on the shortest augmenting path method and genetic algorithm (GA) to solve the MIP. The numerical study is conducted in the end. Numerical result verifies that decision-maker's risk preferences have a huge impact on the structure of supply chain network and the average performance of reliable supply chain network is much better than that of deterministic supply chain network in the presence of risks.
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