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Mathematical Programming for Modelling Green Supply Chains Under Randomness and Fuzziness

Author

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  • Javad Nematian

    (Department of Industrial Engineering, University of Tabriz, Tabriz, Iran)

  • Seyed Salar Ghotb

    (University of Tabriz, Tabriz, Iran)

Abstract

Nowadays by growing concerns about environmental problems, businesses and industries are under pressure to decrease their negative impact on environment, consequently firms and industries have to reconsider about their activities and make their business compatible with environment. So industries should green their supply chains to optimize economic and environmental concerns, but because of uncertainty in the real world like inconsistency of world economy, the process of greening supply chains can be more complex. To optimize total costs and the unfavourable sides of supply chains simultaneously in an uncertain situation, this paper presents a multi-objective mixed integer programming with fuzzy random variables (FRVs) and by using fuzzy theory and fuzzy random chance-constrained programming (FRCCP), the proposed model is converted to deterministic model. This paper can be also suitable for decision making with optimistic, pessimistic and realistic notion. Finally, a numerical example is presented to illustrate the model.

Suggested Citation

  • Javad Nematian & Seyed Salar Ghotb, 2017. "Mathematical Programming for Modelling Green Supply Chains Under Randomness and Fuzziness," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 6(1), pages 56-85, January.
    • Handle: RePEc:igg:jfsa00:v:6:y:2017:i:1:p:56-85
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