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An Optimization Approach for the Coordinated Low-Carbon Design of Product Family and Remanufactured Products

Author

Listed:
  • Qi Wang

    (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Dunbing Tang

    (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Shipei Li

    (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Jun Yang

    (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Miguel A. Salido

    (Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, Camino de Vera s/n 46071, 46022 Valencia, Spain)

  • Adriana Giret

    (Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, Camino de Vera s/n 46071, 46022 Valencia, Spain)

  • Haihua Zhu

    (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Abstract

With increasingly stringent environmental regulations on emission standards, enterprises and investigators are looking for effective ways to decrease GHG emission from products. As an important method for reducing GHG emission of products, low-carbon product family design has attracted more and more attention. Existing research, related to low-carbon product family design, did not take into account remanufactured products. Nowadays, it is popular to launch remanufactured products for environmental benefit and meeting customer needs. On the one hand, the design of remanufactured products is influenced by product family design. On the other hand, the launch of remanufactured products may cannibalize the sale of new products. Thus, the design of remanufactured products should be considered together with the product family design for obtaining the maximum profit and reducing the GHG emission as soon as possible. The purpose of this paper is to present an optimization model to concurrently determine product family design, remanufactured products planning and remanufacturing parameters selection with consideration of the customer preference, the total profit of a company and the total GHG emission from production. A genetic algorithm is applied to solve the optimization problem. The proposed method can help decision-makers to simultaneously determine the design of a product family and remanufactured products with a better trade-off between profit and environmental impact. Finally, a case study is performed to demonstrate the effectiveness of the presented approach.

Suggested Citation

  • Qi Wang & Dunbing Tang & Shipei Li & Jun Yang & Miguel A. Salido & Adriana Giret & Haihua Zhu, 2019. "An Optimization Approach for the Coordinated Low-Carbon Design of Product Family and Remanufactured Products," Sustainability, MDPI, vol. 11(2), pages 1-22, January.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:2:p:460-:d:198337
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    References listed on IDEAS

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    Cited by:

    1. Min Dai & Ziwei Zhang & Adriana Giret & Miguel A. Salido, 2019. "An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints," Sustainability, MDPI, vol. 11(11), pages 1-23, May.
    2. Muneeb, Syed Mohd & Asim, Zainab & Hajiaghaei-Keshteli, Mostafa & Abbas, Haidar, 2023. "A multi-objective integrated supplier selection-production-distribution model for re-furbished products: Towards a circular economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    3. Qi Wang & Peipei Qi & Shipei Li, 2021. "A Concurrence Optimization Model for Low-Carbon Product Family Design and the Procurement Plan of Components under Uncertainty," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    4. Xuhui Xia & Wei Liu & Zelin Zhang & Lei Wang & Jianhua Cao & Xiang Liu, 2019. "A Balancing Method of Mixed-model Disassembly Line in Random Working Environment," Sustainability, MDPI, vol. 11(8), pages 1-16, April.

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