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Graph decomposition based adaptive time-stepping framework for dynamic minimum cost flow
DOI:10.1016/j.eswa.2026.131419.png)
摘要
En 中文
• PDIAM integrates decomposition, adaptive search and online robust optimization • Duality-based model casts minimax flow as tractable LP with uncertainty budget • Decomposition isolates disturbances, adaptive search escapes local optima real time • Simulations on CSTK and real-data show 25.7%+ 1.3% cost savings
期刊
IF:
7.5
论文数:
3.0W
被引数:
10.2W
机构
引用论文
A reinforcement learning approach for reducing traffic congestion using deep Q learning
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IF3.9
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