TY - JOUR
T1 - A bilevel optimisation model for the joint configuration of new and remanufactured products considering specification upgrading of used products
AU - Geda, M. W.
AU - Zheng, Pai
AU - Kwong, C. K.
AU - Tang, Yuk Ming
N1 - Funding Information:
This work was supported by a PhD studentship from The Hong Kong Polytechnic University [project account code: RUNJ] and the National Natural Research Foundation of China [Grant No. 52005424].
Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Bilevel optimisation
KW - Nested bilevel GA
KW - Product design configuration
KW - Remanufactured product
KW - Specification upgrading
UR - http://www.scopus.com/inward/record.url?scp=85160862637&partnerID=8YFLogxK
U2 - 10.1007/s10845-023-02140-1
DO - 10.1007/s10845-023-02140-1
M3 - Journal article
AN - SCOPUS:85160862637
SN - 0956-5515
JO - Journal of Intelligent Manufacturing
JF - Journal of Intelligent Manufacturing
ER -