Optimal Design of Reverse Supply Chain Network for Waste Mobile Phones under Uncertainty

Song, Zuoling; Sun, Hui; Liu, Xinmin; Wang, Manfei

doi:10.1109/icaica50127.2020.9181931

Cited by 1 publication

(3 citation statements)

References 37 publications

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“…Efforts towards applying the reverse logistics practice with the help of artificial intelligence to establish circularity in the economic system have been seen [29,76,77]. Several studies on reverse logistics to achieve CE has been found where researchers focused on faulty products returning tactics [52], optimization of e-waste (concentrating on a mobile phone) recycling [78], assuring product quality to better understand its reusability [79] and the overall automation of reverse logistics process [29].…”

Section: Reverse Logisticsmentioning

confidence: 99%

“…An architecture was developed by them which can efficiently minimize the empty runs of the delivery vehicle and work as a reverse logistics method in the circular economy context. The study of Song et al [78] showed an optimized reverse supply chain network for waste mobile phone recycling as it brought immense harm to the environment and resources. These resources can be recycled, reused and remanufactured to increase the life cycle.…”

Section: Reverse Logisticsmentioning

confidence: 99%

“…In CE, the reverse supply chain process plays an important role by reducing the amount of new waste generation and recycling the existing products. We found two articles that discussed the reverse supply chain [78,87], where authors proposed a design for a reverse supply chain network for waste mobile phones [78] and for automobile parts recycling [87]. Makarova et al [52] presented a decision support system for the supplier of spare parts.…”

Section: Supply Chain Managementmentioning

confidence: 99%

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Machine Learning and Artificial Intelligence in Circular Economy: A Bibliometric Analysis and Systematic Literature Review

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With unorganized, unplanned and improper use of limited raw materials, an abundant amount of waste is being produced, which is harmful to our environment and ecosystem. While traditional linear production lines fail to address far-reaching issues like waste production and a shorter product life cycle, a prospective concept, namely circular economy (CE), has shown promising prospects to be adopted at industrial and governmental levels. CE aims to complete the product life cycle loop by bringing out the highest values from raw materials in the design phase and later on by reusing, recycling, and remanufacturing. Innovative technologies like artificial intelligence (AI) and machine learning(ML) provide vital assistance in effectively adopting and implementing CE in real-world practices. This study explores the adoption and integration of applied AI techniques in CE. First, we conducted bibliometric analysis on a collection of 104 SCOPUS indexed documents exploring the critical research criteria in AI and CE. Forty papers were picked to conduct a systematic literature review from these documents. The selected documents were further divided into six categories: sustainable development, reverse logistics, waste management, supply chain management, recycle & reuse, and manufacturing development. Comprehensive research insights and trends have been extracted and delineated. Finally, the research gap needing further attention has been identified and the future research directions have also been discussed.

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