ArticleComputers & industrial engineering2022
Hybrid combinatorial remanufacturing strategy for medical equipment in the pandemic.
Article in Computers & industrial engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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2 authors.
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Abstract
The COVID-19 pandemic hit the medical supply chain, creating a serious shortage of medical equipment. To meet the urgent demand, one realistic way is to collect abandoned medical equipment and then remanufacture, where the disassembled modules are shared with all stock-keeping units (SKUs) to improve utilization. However, in an emergency, the equipment should be processed sequentially and immediately, which means the decision is short-sighted with limited information. We propose a hybrid combinatorial remanufacturing (HCR) strategy and develop two reinforcement learning frameworks based on Q-learning and double deep Q network to find the optimal recovery option. In the frameworks, we transform HCR problem into a maze exploration game and propose a rule of descending epsilon-greedy selection on reweighted valid actions (DeSoRVA) and
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