4.7 Article

Global reverse supply chain design for solid waste recycling under uncertainties and carbon emission constraint

Journal

WASTE MANAGEMENT
Volume 64, Issue -, Pages 358-370

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.wasman.2017.02.024

Keywords

Reverse supply chain; Solid waste recycling; Global supply chain; Carbon emission

Funding

  1. NPRP award NPRP from the Qatar National Research Fund (a member of The Qatar Foundation) [5-1284-5-198]
  2. Fundamental Research Funds for the Central Universities of China [90YAH16087]
  3. National Science Foundation of China [71273130]
  4. National Natural Science Fund of China [71273131]

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The emergence of concerns over environmental protection, resource conservation as well as the development of logistics operations and manufacturing technology has led several countries to implement formal collection and recycling systems of solid waste. Such recycling system has the benefits of reducing environmental pollution, boosting the economy by creating new jobs, and generating income from trading the recyclable materials. This leads to the formation of a global reverse supply chain (GRSC) of solid waste. In this paper, we investigate the design of such a GRSC with a special emphasis on three aspects; (1) uncertainty of waste collection levels, (2) associated carbon emissions, and (3) challenges posed by the supply chain's global aspect, particularly the maritime transportation costs and currency exchange rates. To the best of our knowledge, this paper is the first attempt to integrate the three above mentioned important aspects in the design of a GRSC. We have used mixed integer-linear programming method along with robust optimization to develop the model which is validated using a sample case study of e-waste management. Our results show that using a robust model by taking the complex interactions characterizing global reverse supply chain networks into account, we can create a better GRSC. The effect of uncertainties and carbon constraints on decisions to reduce costs and emissions are also shown. (C) 2017 Elsevier Ltd. All rights reserved.

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