Multi-period reverse logistics network design for used refrigerators

被引:53
|
作者
John, Sajan T. [1 ]
Sridharan, R. [2 ]
Kumar, P. N. Ram [3 ]
Krishnamoorthy, M. [4 ,5 ]
机构
[1] Viswajyothi Coll Engn & Technol, Muvattupuzha 686670, Kerala, India
[2] Natl Inst Technol Calicut, Mech Engn Dept, Calicut 673601, Kerala, India
[3] Indian Inst Management Kozhikode, QM & OM Area, Calicut 673570, Kerala, India
[4] Monash Univ, Dept Mech & Aerosp Engn, Clayton, Vic 3880, Australia
[5] Univ Queensland, Dept Informat Technol & Elect Engn, St Lucia, Qld 4072, Australia
关键词
Reverse logistics; Network design; Remanufacturing; Repairing; Recycling; Refrigerator; LOOP SUPPLY-CHAIN; PRODUCT-RECOVERY; BENDERS DECOMPOSITION; OPTIMIZATION MODEL; GENETIC ALGORITHM; FACILITY LOCATION; INVENTORY MODELS; CARBON EMISSIONS; UNCERTAINTY; DEMAND;
D O I
10.1016/j.apm.2017.09.053
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper focuses on the design of a multi-stage reverse logistics network for product recovery. Different recovery options such as product remanufacturing, component repairing and material recycling are simultaneously considered. Initially, we propose a mixed integer linear programming model - with a profit maximization objective - for the network design problem. The structure of the product, by way of bill of materials (BOM), is also incorporated into the proposed model in order to analyze the flow at component and material levels. Sensitivity analysis is carried out to study the effects of variations in the values of the input parameters such as product return quantity, unit transportation cost per unit distance, and unit processing cost. The analysis shows that the design decisions of different facilities considerably change even for 5-20%% variations in input parameter values. This led to the development of a refined mathematical model which incorporates variations in the different input parameter values over time. The new model provides a unified design for the entire planning horizon and has been validated with the design of a used refrigerator recovery network. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:311 / 331
页数:21
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