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Green supply chain flow analysis with multi-attribute demand in a multi-period product development environment

Author

Listed:
  • Sahar Porkar

    (Department of Industrial Engineering, Mazandaran University of Science and Technology)

  • Iraj Mahdavi

    (Department of Industrial Engineering, Mazandaran University of Science and Technology)

  • Behzad Maleki Vishkaei

    (Department of Industrial Engineering, Mazandaran University of Science and Technology)

  • Milad Hematian

    (Department of Industrial Engineering, Mazandaran University of Science and Technology)

Abstract

Green supply chain management is based on performing environmental management into supply chain network in order to decrease the environmental side effects in the product life cycle. So, in this paper, a bi-objective nonlinear programming for an integrated forward/reverse logistics network with the aim of increasing total profit of the network and maximizing the score of green design and quality indicators and green scrap score is discussed. Quality and green design indicators are considered for the forward network and the green scrap score are defined for scrapped products collected and disassembled in the reverse network. The mentioned network includes three echelons in the forward flow (production centers (factories), distribution centers, and customer zones) and three echelons in the reverse flow (collection/disassembly centers, recycling centers, and disposal centers). The main contribution of this study is to consider green design indicators and quality indicators for developing final products. Furthermore, in the model of this research, some constraints are regarded to determine the amount of paper and plastic consumption in the packaging of the products. After presenting the considered model, Multi-objective Particle Swarm Optimization and Non-dominated Sorting Genetic (NSGA-II) meta-heuristic Algorithms are proposed to find a set of Pareto-optimal solutions. Then, their output is compared through some samples with different sizes to prove their workability.

Suggested Citation

  • Sahar Porkar & Iraj Mahdavi & Behzad Maleki Vishkaei & Milad Hematian, 2020. "Green supply chain flow analysis with multi-attribute demand in a multi-period product development environment," Operational Research, Springer, vol. 20(3), pages 1405-1435, September.
    • Handle: RePEc:spr:operea:v:20:y:2020:i:3:d:10.1007_s12351-018-0382-5
    DOI: 10.1007/s12351-018-0382-5
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    References listed on IDEAS

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    1. Fleischmann, Moritz & Bloemhof-Ruwaard, Jacqueline M. & Dekker, Rommert & van der Laan, Erwin & van Nunen, Jo A. E. E. & Van Wassenhove, Luk N., 1997. "Quantitative models for reverse logistics: A review," European Journal of Operational Research, Elsevier, vol. 103(1), pages 1-17, November.
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    4. Schultmann, Frank & Zumkeller, Moritz & Rentz, Otto, 2006. "Modeling reverse logistic tasks within closed-loop supply chains: An example from the automotive industry," European Journal of Operational Research, Elsevier, vol. 171(3), pages 1033-1050, June.
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    Cited by:

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    2. Moghadam, Saman Salehi & Gholamian, Mohammad Reza & Zahedi, Rahim & Shaqaqifar, Maziar, 2024. "Designing a multi-purpose network of sustainable and closed-loop renewable energy supply chain, considering reliability and circular economy," Applied Energy, Elsevier, vol. 369(C).

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