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• W4324380818 abstract "This study considers the problem of inventory and scheduling decisions on a reusable transport item (RTI) sharing platform with the collaborative recovery of used RTIs and replenishment of products in a two-tier container management centre (CMC). The products (packaged as full RTIs) are pre-positioned at the regional CMC (R-CMC), and empty RTIs are stored at the CMC hub. Moreover, the CMC replenishes the products and recycles RTIs respectively and periodically. The RTI and products are a set of complementary products, and the replenishment task requires sufficient empty RTIs in stock. Untimely and insufficient RTI returns without considering product inventory changes often result in RTI out-of-stock situations that harm the customer's lean productivity. This paper proposes a machine learning and simulation optimisation (MSO) decision framework to collaboratively assist RTI inventory and scheduling decisions in a two-tier CMC. Based on a case study, we can conclude the decision framework has better performance on the profitability and inventory control capability. Moreover, different inventory and scheduling parameter settings in the two-tier CMCs impact the platform's profitability to derive corresponding management insights, and a decision system can be built based on the above framework." @default.
• W4324380818 created "2023-03-16" @default.
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• W4324380818 date "2023-03-15" @default.
• W4324380818 modified "2023-09-27" @default.
• W4324380818 title "Integrated inventory control and scheduling decision framework for packaging and products on a reusable transport item sharing platform" @default.
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• W4324380818 doi "https://doi.org/10.1080/00207543.2023.2187243" @default.
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