An integrated MCDM approach considering demands-matching for reverse logistics

JOURNAL OF CLEANER PRODUCTION

卷:208

Article

Wang, Han¹  Jiang, Zhigang²  Zhang, Hua²  Wang, Yan³  Yang, Yihua⁴  Li, Yi⁴ 

[1] Wuhan Univ Sci & Technol, Hubei Key Lab Mech Transmiss & Mfg Engn, Wuhan 430081, Hubei, Peoples R China

[2] Wuhan Univ Sci & Technol, Key Lab Met Equipment & Control Technol, Wuhan 430081, Hubei, Peoples R China

[3] Univ Brighton, Dept Comp Engn & Math, Brighton BN2 4GJ, E Sussex, England

[4] Sevalo Construct Machinery Remfg Co Ltd, Wuhan 430040, Hubei, Peoples R China

关键词: Reverse logistics;    Multiple criteria decision making;    Demands matching;    Damage level;    Remaining service life;   

DOI  :  10.1016/j.jclepro.2018.10.131

来源: Elsevier

【 摘 要 】

Reverse logistics (RL) has been regarded as a key driving force for remanufacturing. However, there are great uncertainties in terms of quality and quantity of used components for RL. There are also complexities in suppliers and operations. These make decision-making of RL very complex. In order to identify the best collection mode for used components, a demand-matching oriented Multiple Criteria Decision Making (MCDM) method is established. In this method, the damage level and remaining service life are firstly incorporated into the evaluation criteria of reuse modes, then a hybrid method (AHP-EW) that integrates Analytic Hierarchy Process (AHP) and Entropy Weight (EW) method is applied to derive criteria weights and the grey Multi-Attributive Border Approximation Area Comparison (MABAC) is adopted to rank the collection modes. Finally, sensitivity analysis is implemented to test the stability of the proposed method, and a demands-matching method is proposed to validate and evaluate the feasibility of the optimal alternative. The collection of used pressurizers is taken as case study to validate the applicability of the proposed model. The results showed the effectiveness of the proposed method in MCDM of RL. Crown Copyright (C) 2018 Published by Elsevier Ltd. All rights reserved.

【 授权许可】

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