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Fuzzy chance-constrained programming model for a multi-echelon reverse logistics network for household appliances

Author

Listed:
  • L K Chu

    (The University of Hong Kong)

  • Y Shi

    (The University of Hong Kong)

  • S Lin

    (Tianjin University)

  • D Sculli

    (The University of Hong Kong)

  • J Ni

    (The University of Hong Kong)

Abstract

Efficient planning and design of an appropriate reverse logistics network is crucial to the economical collection and disposal of scrapped household appliances and electrical products. Such systems are commonly modelled as mixed-integer programs, whose solutions will determine the location of individual facilities that optimize material flow. One of the major drawbacks of current models is that they do not adequately address the important issue of uncertainty in demand and supply. Another deficiency in current models is that they are restricted to a two-echelon system. This study addresses these deficiencies by embodying such uncertainties in the model using the technique of fuzzy-chance constrained programming, and by extending the model to a three-echelon system. A heuristic in the form of a hybrid genetic algorithm is then employed to generate low-cost solutions. The overall objective is to find economical solutions to the general problem of determining the volume of appliances to be moved between the three echelons of customer base to collection sites, collection sites to disposal centres and disposal centre to landfill centre/remanufacturing centre; and to the problems of positioning the disposal centres and the landfill centre/remanufacturing centres within the problem domain. A case example in China is presented and the quality and robustness of the solutions are explored through sensitivity analysis.

Suggested Citation

  • L K Chu & Y Shi & S Lin & D Sculli & J Ni, 2010. "Fuzzy chance-constrained programming model for a multi-echelon reverse logistics network for household appliances," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(4), pages 551-560, April.
    • Handle: RePEc:pal:jorsoc:v:61:y:2010:i:4:d:10.1057_jors.2008.162
    DOI: 10.1057/jors.2008.162
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    References listed on IDEAS

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    1. Min, Hokey & Jeung Ko, Hyun & Seong Ko, Chang, 2006. "A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns," Omega, Elsevier, vol. 34(1), pages 56-69, January.
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