An integrated model for closed-loop supply chain configuration and supplier selection: Multi-objective approach

被引:203
作者
Amin, Saman Hassanzadeh [1 ]
Zhang, Guogqing [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
Supplier selection; Reverse logistics (RL); Closed-loop supply chain (CLSC); Multi objective programming; Fuzzy sets theory (FST); DECISION-MAKING PROCESS; ANALYTIC HIERARCHY PROCESS; REVERSE LOGISTICS; PRODUCT RECOVERY; VENDOR SELECTION; SUPPORT-SYSTEM; NETWORK DESIGN; MANAGEMENT; CRITERIA; TOPSIS;
D O I
10.1016/j.eswa.2011.12.056
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Reverse logistics consists of all operations related to the reuse of products. External suppliers are one of the important members of reverse logistics and closed loop supply chain (CLSC) networks. However in CLSC network configuration models, suppliers are assessed based on purchasing cost and other factors such as on-time delivery are ignored. In this research, a general closed loop supply chain network is examined that includes manufacturer, disassembly, refurbishing, and disposal sites. Meanwhile, it is managed by the manufacturer. We propose an integrated model which has two phases. In the first phase, a framework for supplier selection criteria in RL is proposed. Besides, a fuzzy method is designed to evaluate suppliers based on qualitative criteria. The output of this stage is the weight of each supplier according to each part. In the second phase, we propose a multi objective mixed-integer linear programming model to determine which suppliers and refurbishing sites should be selected (strategic decisions), and find out the optimal number of parts and products in CLSC network (tactical decisions). The objective functions maximize profit and weights of suppliers, and one of them minimizes defect rates. To our knowledge, this model is the first effort to consider supplier selection, order allocation, and CLSC network configuration, simultaneously. The mathematical programming model is validated through numerical analysis. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:6782 / 6791
页数:10
相关论文
共 48 条
[1]   Supplier selection and order lot sizing modeling: A review [J].
Aissaoui, Najla ;
Haouari, Mohamed ;
Hassini, Elkafi .
COMPUTERS & OPERATIONS RESEARCH, 2007, 34 (12) :3516-3540
[2]   Supplier selection and order allocation based on fuzzy SWOT analysis and fuzzy linear programming [J].
Amin, Saman Hassanzadeh ;
Razmi, Jafar ;
Zhang, Guoqing .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (01) :334-342
[3]   An integrated fuzzy model for supplier management: A case study of ISP selection and evaluation [J].
Amin, Saman Hassanzadeh ;
Razmi, Jafar .
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (04) :8639-8648
[4]  
[Anonymous], J PURCHASING
[5]  
[Anonymous], FUZZY MATH PROGRAMMI
[6]   A fuzzy TOPSIS methodology to support outsourcing of logistics services [J].
Bottani, Eleonora ;
Rizzi, Antonio .
SUPPLY CHAIN MANAGEMENT-AN INTERNATIONAL JOURNAL, 2006, 11 (04) :294-308
[7]   Global supplier development considering risk factors using fuzzy extended AHP-based approach [J].
Chan, Felix T. S. ;
Kumar, Niraj .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2007, 35 (04) :417-431
[8]   A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach [J].
Chou, Shuo-Yan ;
Chang, Yao-Hui .
EXPERT SYSTEMS WITH APPLICATIONS, 2008, 34 (04) :2241-2253
[9]  
De Boer L., 2001, EUROPEAN J PURCHASIN, V7, P75, DOI [DOI 10.1016/S0969-7012(00)00028-9, 10.1016/S0969-7012(00)00028-9]
[10]  
Demirtas EA, 2008, OMEGA, V36, P509