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Network restructuring for dynamic flow improvement
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AI
DOI：10.1007/s10479-025-06496-w.png)
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摘要
En 中文
The increasing number of frequent disasters caused by global climatic unbalances, earthquakes and flooding highly demand scientific emergency plannings of the urban cities. As many urban metropolitan areas are suffered by increasing entry of vehicles into very classical narrow-road city network within weak infrastructure, the traffic move in case of emergencies becomes horrible, particularly at bottleneck road sections. Improving their capability is subject to the budgetary constraints. In this paper, we consider the bottleneck congestion problem and present interesting mathematical formulations where speed and thereby arc travel times are adjusted so that the traffic congestion at bottlenecks are relaxed. Polynomial time algorithms are presented with their correctness proofs for the quickest flow and priority based flow maximization problems. The problem is solved in two phases. In the first phase, the model with objective of priority based flow maximization allows storage of excess flow at intermediate nodes. In addition, the model is extended to the quickest flow objective which pushes all stored flow taking the minimum additional time to the final destination. Moreover, both models are also solved with lane reversal strategy. By applying these combined approaches (flow maximization, time minimization, excess flow storage, pushing the excess flow to the sink and contraflow), the solution is improved significantly. Some illustrations are highlighted that shows the novelty of the integrated new models.
Keyword:
Network optimization
Evacuation planning
Flow maximization
Quickest flow
Contraflow
期刊
IF:
4.5
论文数:
8.0K
被引数:
2.1W