Scipediacontent: Scipediacontent moved page Review 616962998453 to Feng et al 2026a

2026-03-18T10:32:16Z

Scipediacontent moved page Review 616962998453 to Feng et al 2026a

Scipediacontent: Scipediacontent moved page Draft content 888238071 to Review 616962998453

2026-03-18T09:00:04Z

Scipediacontent moved page Draft content 888238071 to Review 616962998453

Scipediacontent: Created page with " == Abstract ==
As global environmental challenges intensify, circular economy (CE) has emerged as a critical pathway for sustainable development. This study proposes a de..."

2026-03-18T08:59:40Z

Created page with " == Abstract == <p>As global environmental challenges intensify, circular economy (CE) has emerged as a critical pathway for sustainable development. This study proposes a de..."

New page

== Abstract ==

<p>As global environmental challenges intensify, circular economy (CE) has emerged as a critical pathway for sustainable development. This study proposes a deep learning-based CE supply chain network design framework that optimizes resource allocation, reduces waste, and improves sustainability. The framework employs graph convolutional networks, long shortterm memory networks, and multi-head attention mechanisms to capture topological, temporal, and multi-dimensional supply chain features. An improved NSGA-III algorithm achieves coordinated balance among economic, environmental, social, and circularity objectives. A comprehensive sustainability evaluation system provides quantitative assessment tools. Experimental validation using real data from 15 enterprises across five industries shows the deep learning model achieves 89.2% prediction accuracy on test sets, representing 16.1% improvement over baselines and 67.9% improvement in computational efficiency. The optimized network achieves 32.4% waste reduction, 28.7% resource efficiency improvement, 25.3% cost reduction, 68.5% material circulation rate, and 89.2% network efficiency. This research contributes to theoretical understanding and provides practical guidance for manufacturing enterprises’ transition to CE, supporting sustainable development goals.OPEN ACCESS Received: 27/09/2025 Accepted: 17/11/2025 Published: 20/03/2026</p>

== Document ==
<pdf>Media:Draft_content_888238071-4323-document.pdf</pdf>

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Feng et al 2026a - Revision history

Scipediacontent: Scipediacontent moved page Review 616962998453 to Feng et al 2026a

Scipediacontent: Scipediacontent moved page Draft content 888238071 to Review 616962998453

Scipediacontent: Created page with " == Abstract == As global environmental challenges intensify, circular economy (CE) has emerged as a critical pathway for sustainable development. This study proposes a de..."

Scipediacontent: Created page with " == Abstract ==
As global environmental challenges intensify, circular economy (CE) has emerged as a critical pathway for sustainable development. This study proposes a de..."