Modular recycling supply chain under uncertainty: a robust optimisation approach

Shahparvari, S, Chhetri, P, Chan, C and Asefi, H 2018, 'Modular recycling supply chain under uncertainty: a robust optimisation approach', The International Journal of Advanced Manufacturing Technology, vol. 96, no. 14, pp. 915-934.


Document type: Journal Article
Collection: Journal Articles

Title Modular recycling supply chain under uncertainty: a robust optimisation approach
Author(s) Shahparvari, S
Chhetri, P
Chan, C
Asefi, H
Year 2018
Journal name The International Journal of Advanced Manufacturing Technology
Volume number 96
Issue number 14
Start page 915
End page 934
Total pages 20
Publisher Springer
Abstract It is estimated that recycling can avert approximately 50% annual landfill cost, while simultaneously recovering lost materials valued at 4 to 9.5% of the total logistics network cost. This study proposes a robust integrated reverse logistics supply chain planning model with a modular product design at different quality levels. A mixed-integer programming (MIP) model is formulated to maximise the profit by considering the collection of returned products, the recovery of modules and the proportion of the product mix at different quality levels. This paper proposes the collection of returnable items (end-oflife, defective and under-warranty products) through retail outlets and the appropriate recovery of modules to manage these using a network of recovery service providers. The modular product design approach is adopted to create design criteria that provide an improved recovery process at a lower cost. This robust model seeks solutions close to the mathematically optimal solutions for a set of alternative scenarios identified by a decision-maker. The efficacy of the proposed model is evaluated by a given set of variously sized numerical expressions and sensitivity analyses. A robust solution is found that appraises the impact of two major sources of uncertainty, demand rate and the volume of returned products of a key recycled material.
Subject Logistics and Supply Chain Management
Road Transportation and Freight Services
Keyword(s) Reverse logistics (RL) · Robust optimisation · Uncertainty environment · Closed-loop supply chain network · MIP model
DOI - identifier 10.1007/s00170-017-1530-4
ISSN 0268-3768
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