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DfMA-Oriented Rebar Design Optimization for Reinforced Concrete Slabs Using a Hybrid Mechanism Integrating Graph Neural Networks and Metaheuristic Algorithms

dc.contributor.authorLi, Mingkai
dc.contributor.authorLin, Fangzhou
dc.contributor.authorWang, Tao
dc.contributor.authorHu, Difeng
dc.contributor.authorWang, Hanmo
dc.contributor.authorWang, Boyu
dc.contributor.authorCheng, Jack C. P.
dc.date.accessioned2026-08-20T21:28:43Z
dc.date.available2026-08-20T21:28:43Z
dc.date.copyright2026/05/24
dc.date.issued2026
dc.identifier.otherJCCEE5.CPENG-7477.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314521
dc.description.abstractAbstractReinforced concrete (RC) slabs are fundamental structural components in buildings and infrastructure, providing load-bearing capacity and overall stability. Optimizing rebar design for RC slabs is crucial for balancing structural performance, ...
dc.publisherAmerican Society of Civil Engineers
dc.titleDfMA-Oriented Rebar Design Optimization for Reinforced Concrete Slabs Using a Hybrid Mechanism Integrating Graph Neural Networks and Metaheuristic Algorithms
dc.typeJournal Article
dc.journal.volume40
dc.journal.issue5
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-7477
dc.journal.fristpage04026053-1
dc.journal.lastpage04026053-16
dc.page16
dc.treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 005
dc.contenttypeFulltext


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