Modular recycling supply chain under uncertainty: a robust optimisation approach

  • Shahrooz Shahparvari
  • Prem Chhetri
  • Caroline Chan
  • Hossein Asefi


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-of-life, 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.


Reverse logistics (RL) Robust optimisation Uncertainty environment Closed-loop supply chain network MIP model 


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© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Shahrooz Shahparvari
    • 1
  • Prem Chhetri
    • 1
  • Caroline Chan
    • 1
  • Hossein Asefi
    • 2
  1. 1.School of Business IT & Logistics, College of BusinessRMIT UniversityMelbourneAustralia
  2. 2.School of Civil and Environmental EngineeringThe University of New South WalesSydneyAustralia

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