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| Robust Optimization of Dual-recovery Remanufacturing Supply Chain Considering Incentive Compatibility Under an Improved Algorithm |
| WANG Zhen, YE Chunming, GUO Jianquan
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| School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China |
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Abstract To study the impact of government subsidies on different recycling channels in the new energy vehicle remanufacturing supply chain, a multi-objective model under dual recycling channels is established, an improved robust optimization method is used to solve the problem of uncertainty in demand and recycling volume during recycling, and a convolutional neural network (Conv-GLU network) method is proposed to solve the model. By comparing the performance of online and offline recycling channels, joint recycling channels and recycling channels under government intervention, the multi-objective optimization under government intervention is optimal. Therefore, the government can reasonably intervene in recycling under the background of big data to help new energy vehicle enterprises establish a dual recycling channel remanufacturing green supply chain.
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Received: 06 October 2023
Published: 09 October 2025
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