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A bilevel optimisation model for the joint configuration of new and remanufactured products considering specification upgrading of used products

Author

Listed:
  • M. W. Geda

    (Laboratory for Artificial Intelligence in Design)

  • Pai Zheng

    (The Hong Kong Polytechnic University)

  • C. K. Kwong

    (The Hong Kong Polytechnic University)

  • Yuk Ming Tang

    (The Hong Kong Polytechnic University)

Abstract

The joint optimisation of product design configuration (PDC) for new and remanufactured products involves specification upgrading for parts recovered from used product returns. Reversely, the specification upgrading decision for used parts/modules is also affected by the original specifications selected for parts/modules during the new product design process. Hence, the joint optimisation of PDC for both new and remanufactured products entails a hierarchical decision framework, of which scarcely any study involves the specification upgrading concerns. To fill this gap, this paper proposes a bilevel optimisation model that involves two-level decision-making. The upper level handles the configuration of new product variants to maximise the shared surplus of new product offerings. Meanwhile, the lower-level deals with the configuration and specification upgrading of remanufactured product variants to maximise the shared surplus of remanufactured product offerings. A non-linear integer bilevel programming is further presented to model the hierarchical optimisation problem, to solve which a nested bilevel genetic algorithm is also proposed. Furthermore, a case study involving configuration design for new and remanufactured mobile phone variants is conducted to validate the proposed model. Four scenarios are investigated to examine the effects of model parameters on the optimal solutions with the simulation result given at last.

Suggested Citation

  • M. W. Geda & Pai Zheng & C. K. Kwong & Yuk Ming Tang, 2024. "A bilevel optimisation model for the joint configuration of new and remanufactured products considering specification upgrading of used products," Journal of Intelligent Manufacturing, Springer, vol. 35(5), pages 2175-2191, June.
    • Handle: RePEc:spr:joinma:v:35:y:2024:i:5:d:10.1007_s10845-023-02140-1
    DOI: 10.1007/s10845-023-02140-1
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    References listed on IDEAS

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    1. Michalek, Jeremy J. & Ebbes, Peter & Adigüzel, Feray & Feinberg, Fred M. & Papalambros, Panos Y., 2011. "Enhancing marketing with engineering: Optimal product line design for heterogeneous markets," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 1-12.
    2. Gang Du & Yi Xia & Roger J. Jiao & Xiaojie Liu, 2019. "Leader-follower joint optimization problems in product family design," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1387-1405, March.
    3. Leandro Gauss & Daniel P. Lacerda & Paulo A. Cauchick Miguel, 2021. "Module-based product family design: systematic literature review and meta-synthesis," Journal of Intelligent Manufacturing, Springer, vol. 32(1), pages 265-312, January.
    4. Wang, Danping & Du, Gang & Jiao, Roger J. & Wu, Ray & Yu, Jianping & Yang, Dong, 2016. "A Stackelberg game theoretic model for optimizing product family architecting with supply chain consideration," International Journal of Production Economics, Elsevier, vol. 172(C), pages 1-18.
    5. Du, Gang & Jiao, Roger J. & Chen, Mo, 2014. "Joint optimization of product family configuration and scaling design by Stackelberg game," European Journal of Operational Research, Elsevier, vol. 232(2), pages 330-341.
    6. Xiaojie Liu & Gang Du & Roger J. Jiao, 2017. "Bilevel joint optimisation for product family architecting considering make-or-buy decisions," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 5916-5941, October.
    7. Mohit Goswami & Yash Daultani & M.K. Tiwari, 2017. "An integrated framework for product line design for modular products: product attribute and functionality-driven perspective," International Journal of Production Research, Taylor & Francis Journals, vol. 55(13), pages 3862-3885, July.
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