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Portfolio optimisation of material purchase considering supply risk – A multi-objective programming model
International Journal of Production Economics ( IF 9.8 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.ijpe.2020.107803
Jun Hao , Jianping Li , Dengsheng Wu , Xiaolei Sun

Abstract For the sake of better coping with the problem of material procurement, a multi-objective optimisation model was established in a systematic analysis framework for material procurement considering supply risk. First, this paper combs and identifies supply risk factors and constructs a supply risk evaluation system from the dimensions of quality, price, delivery, service and technology. Second, based on the linguistic scale and fuzzy theory, this paper measures the supply risk of candidate suppliers and estimates the relevant parameters of the multi-objective optimisation model by using the triangular fuzzy numbers. In addition, an improved non-dominated sorting genetic algorithm II (NSGA-II) is utilized in this paper to solve the multi-objective model, since traditional intelligent algorithms have slow convergence speed and are easily trapping into local optimisation. Finally, this paper conducts simulation experiments by setting three types of decision-makers with different risk preferences and provides material procurement combination schemes in different scenarios. Through numerical simulation experiments, it was verified that the optimisation model established in this paper was feasible and useful for the selection of candidate suppliers and the portfolio optimisation of material procurement.

中文翻译:

考虑供应风险的物料采购组合优化——多目标规划模型

摘要 为了更好地应对物资采购问题,在考虑供应风险的物资采购系统分析框架中,建立了多目标优化模型。首先,本文梳理识别供应风险因素,从质量、价格、交期、服务、技术等维度构建供应风险评价体系。其次,基于语言尺度和模糊理论,本文利用三角模糊数来衡量候选供应商的供应风险,并估计多目标优化模型的相关参数。此外,本文利用改进的非支配排序遗传算法 II (NSGA-II) 来求解多目标模型,因为传统的智能算法收敛速度慢,容易陷入局部优化。最后,本文通过设置三类不同风险偏好的决策者进行模拟实验,提供不同场景下的物资采购组合方案。通过数值模拟实验,验证了本文建立的优化模型对于候选供应商的选择和物料采购的组合优化是可行和有用的。
更新日期:2020-12-01
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