Reverse logistics network design for product reuse, remanufacturing, recycling and refurbishing under uncertainty

[Display omitted] •A new reverse logistics network with six various types of facilities designed.•Two stage stochastic condition with multi products is considered.•Multi supplier is investigated to supply shortage of modules in remanufacturing.•Hybrid algorithm is developed to reduce computational t...

Full description

Saved in:
Bibliographic Details
Published in:Journal of manufacturing systems 2021-07, Vol.60, p.473-486
Main Authors: Shafiee Roudbari, Erfan, Fatemi Ghomi, S.M.T., Sajadieh, Mohsen S.
Format: Article
Language:English
Subjects:
Hybrid algorithm
Refurbishing and recycle
Reuse and remanufacturing
Reverse logistics
Supply chain network design
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:[Display omitted] •A new reverse logistics network with six various types of facilities designed.•Two stage stochastic condition with multi products is considered.•Multi supplier is investigated to supply shortage of modules in remanufacturing.•Hybrid algorithm is developed to reduce computational time.•A problem in a medical equipment company studied to verify the model. With the improvement of the quality of life in human society, the need to use more natural resources is felt more than ever. In this regard, much research has been done on restoring depreciated and consumed products to the supply chain; many factors, including the quality of returned products, can significantly impact how the reverse logistics network will be used. The two-stage stochastic mixed-integer programming model proposed in this paper considers various processes of recovering recyclable products, including reuse, refurbishing, remanufacturing, recycling, and selling spare parts. Also, considering uncertainty on quality and quantity of returned products, product variety, and bill of material are model features. Due to the computational complexity of large-scale problems, such problems require considerable time to solve. To tackle this issue, a hybrid algorithm constructed by a genetic algorithm and branch and cut algorithm (with CPLEX solver) has been introduced, which can significantly reduce the solution time. Finally, the algorithm is applied to a real-world problem to design a reverse logistics network for a small-size laboratory equipment manufacturer.
ISSN:0278-6125
1878-6642
DOI:10.1016/j.jmsy.2021.06.012