A three-stage model for closed-loop supply chain configuration under uncertainty

被引:79
作者
Amin, Saman Hassanzadeh [1 ]
Zhang, Guoqing [1 ]
机构
[1] Univ Windsor, Dept Ind & Mfg Syst Engn, Windsor, ON N9B 3P4, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
reverse logistics (RL); closed-loop supply chain (CLSC); uncertainty; mixed-integer nonlinear programming (MINLP); fuzzy sets theory (FST); QUALITY FUNCTION DEPLOYMENT; REVERSE LOGISTICS NETWORK; QUANTITATIVE MODELS; FACILITY LOCATION; SELECTION; PRODUCT; DESIGN; MANAGEMENT; SYSTEM; OPTIMIZATION;
D O I
10.1080/00207543.2012.693643
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, a general closed-loop supply chain (CLSC) network is configured which consists of multiple customers, parts, products, suppliers, remanufacturing subcontractors, and refurbishing sites. We propose a three-stage model including evaluation, network configuration, and selection and order allocation. In the first stage, suppliers, remanufacturing subcontractors, and refurbishing sites are evaluated based on a new quality function deployment (QFD) model. The proposed QFD model determines the relationship between customer requirements, part requirements, and process requirements. In addition, the fuzzy sets theory is utilised to overcome the uncertainty in the decision-making process. In the second stage, the closed-loop supply chain network is configured by a stochastic mixed-integer nonlinear programming model. It is supposed that demand is an uncertain parameter. Finally in the third stage, suppliers, remanufacturing subcontractors, and refurbishing sites are selected and order allocation is determined. To this end, a multi-objective mixed-integer linear programming model is presented. An illustrative example is conducted to show the process. The main novel innovation of the proposed model is to consider the CLSC network configuration and selection process simultaneously, under uncertain demand and in an uncertain decision-making environment.
引用
收藏
页码:1405 / 1425
页数:21
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