Dynamic Network Flow Optimization for Real-time Evacuation Reroute Planning under Multiple Road Disruptions

2021 ◽  
pp. 107644
Author(s):  
Ayda Darvishan ◽  
Gino J. Lim
Keyword(s):  
Real Time ◽  
Network Flow ◽  
Dynamic Network ◽  
Flow Optimization ◽  
Dynamic Network Flow ◽  
Network Flow Optimization

scholarly journals A survey on network contraflow evacuation planningproblems

2015 ◽  
Vol 3 ◽  
pp. 44-53
Author(s):  
Phanindra Prasad Bhandari ◽  
Shree Ram Khadka
Keyword(s):  
Network Flow ◽  
Dynamic Network ◽  
Route Planning ◽  
Evacuation Planning ◽  
Solution Strategies ◽  
General Network ◽  
Evacuation Route Planning ◽  
Network Flow Optimization ◽  
Evacuation Route ◽  
Potential Remedy

Evacuation planning is becoming crucial due to an increasing number of natural and human-created disasters over last few decades. One of the efficient ways to model the evacuation situation is a network flow optimization model. This model captures most of the necessities of the evacuation planning. Moreover, dynamic network contraflow modeling is considered a potential remedy to decrease the congestion due to its direction reversal property and it addresses the challenges of evacuation route planning. However, there do not exist satisfactory analytical results to this model for general network. In this paper, it is tried to provide an annotated overview on dynamic network contraflow problems related to evacuation planning and to incorporate models and solution strategies to them developed in this field to date.

scholarly journals Optimum Flows in Directed Bipartite Dynamic Network. The Static Approach

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Combinatorial Optimization ◽  
Network Flow ◽  
Dynamic Network ◽  
Time Varying ◽  
Flow Models ◽  
Dynamic Network Flow ◽  
Static Approach ◽  
Network Flow Models ◽  
Discrete Values ◽  
Time Expanded Network

The theory of flows is one of the most important parts of Combinatorial Optimization and it has various applications. In this paper we study optimum (maximum or minimum) flows in directed bipartite dynamic network and is an extension of article [9]. In practical situations, it is easy to see many time-varying optimum problems. In these instances, to account properly for the evolution of the underlying system overtime, we need to use dynamic network flow models. When the time is considered as a variable discrete values, these problems can be solved by constructing an equivalent, static time expanded network. This is a static approach.

scholarly journals On self-tuning networks-on-chip for dynamic network-flow dominance adaptation

2014 ◽  
Vol 13 (2s) ◽  
pp. 1-21 ◽  
Author(s):  
Xiaohang Wang ◽  
Mei Yang ◽  
Yingtao Jiang ◽  
Peng Liu ◽  
Masoud Daneshtalab ◽  
...  
Keyword(s):  
Network Flow ◽  
Dynamic Network ◽  
Networks On Chip ◽  
Dynamic Network Flow ◽  
Self Tuning ◽  
On Chip

scholarly journals Cut Redistribution and Insertion for Advanced 1-D Layout Design via Network Flow Optimization

2018 ◽  
Vol 26 (9) ◽  
pp. 1613-1626
Author(s):  
Ye Zhang ◽  
Wenlong Lyu ◽  
Wai-Shing Luk ◽  
Fan Yang ◽  
Hai Zhou ◽  
...  
Keyword(s):  
Network Flow ◽  
Layout Design ◽  
Flow Optimization ◽  
Network Flow Optimization

scholarly journals Scalable Bayesian Modeling, Monitoring, and Analysis of Dynamic Network Flow Data

2018 ◽  
Vol 113 (522) ◽  
pp. 519-533 ◽  
Author(s):  
Xi Chen ◽  
Kaoru Irie ◽  
David Banks ◽  
Robert Haslinger ◽  
Jewell Thomas ◽  
...  
Keyword(s):  
Bayesian Modeling ◽  
Network Flow ◽  
Dynamic Network ◽  
Flow Data ◽  
Dynamic Network Flow
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