作者
Yongting Tian,Shouxu Song,Dan Zhou,Ruirui Yang,Chen Wei
摘要
AbstractThis article underscores the necessity for sustainable and environmentally friendly manufacturing practices in product family configuration (PFC) projects, which are paramount to the global economy. Nevertheless, conventional approaches often fixate solely on design aspects, overlooking downstream supply chain configuration (SCC) considerations and the corresponding environmental benefits. Consequently, there is an escalating demand for an integrated optimisation approach that encompasses both PFC and SCC to realise economic and environmental advantages. This study delves into a methodology that integrates blockchain smart contracts as binary 0–1 variables with waste recycling and utilisation, yielding a comprehensive multi-objective model. The proposed methodology seamlessly incorporates considerations for both PFC and SCC. Furthermore, a nested leader-follower optimisation algorithm, based on the non-dominated sorting genetic algorithm-II (NSGA-II), has been devised with the objective of achieving triple benefits: augmented profits, maintenance revenue, and diminished environmental emissions. In conclusion, this research contributes to the advancement of sustainable collaborative optimisation through the innovative utilisation of blockchain smart contracts and multi-level modelling. To demonstrate the effectiveness of the proposed methodology, it is applied to a 60 KW DC electric vehicle (EV) charging piles, accompanied by a sensitivity analysis to assess its management implications.KEYWORDS: Product family configurationsupply chain configurationleader-follower optimisationnon-dominated sorting genetic algorithm-IIDC charging piles AcknowledgmentsThe authors would like to thank Keda Intelligent Technology Co., Ltd. (Hefei City, Anhui Province, China) for supporting some of the data in this study. Furthermore, the author extends thanks to the collaborating entities, namely, the Chinese Academy of Environmental Sciences, Solid Waste and Chemical Management Technology Center under the Ministry of Ecology and Environment, and China National Electrical Equipment Research Institute Co., Ltd., for their generous support.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work has been funded by the National Key R & D Program in China [grant number 2019YFC1908005].