Dynamic network flows for generalized kirchhoff law

1996 ◽  
Vol 32 (3) ◽  
pp. 393-397 ◽  
Author(s):  
V. V. Ostapenko ◽  
A. I. Pavlygin
Keyword(s):  
Network Flows ◽  
Dynamic Network ◽  
Dynamic Network Flows

scholarly journals On solving continuous-time dynamic network flows

2011 ◽  
Vol 53 (3) ◽  
pp. 497-524 ◽  
Author(s):  
S. Mehdi Hashemi ◽  
Ebrahim Nasrabadi
Keyword(s):  
Continuous Time ◽  
Network Flows ◽  
Dynamic Network ◽  
Time Dynamic ◽  
Dynamic Network Flows

Minimum Convex Cost Dynamic Network Flows

1984 ◽  
Vol 9 (2) ◽  
pp. 190-207 ◽  
Author(s):  
James B. Orlin
Keyword(s):  
Network Flows ◽  
Dynamic Network ◽  
Convex Cost ◽  
Dynamic Network Flows

A SOLUTION TO THE INVERSE MINIMUM CUT PROBLEM IN DYNAMIC NETWORK FLOWS

2016 ◽  
Vol 49 (4) ◽  
pp. 267-285
Author(s):  
Hajar Banikhademi ◽  
Hasan Salehi Fathabadi
Keyword(s):  
Network Flows ◽  
Dynamic Network ◽  
Minimum Cut ◽  
Dynamic Network Flows ◽  
Minimum Cut Problem

Maximal, Lexicographic, and Dynamic Network Flows

1973 ◽  
Vol 21 (2) ◽  
pp. 517-527 ◽  
Author(s):  
Edward Minieka
Keyword(s):  
Network Flows ◽  
Dynamic Network ◽  
Dynamic Network Flows

Flow location (FlowLoc) problems: dynamic network flows and location models for evacuation planning

2011 ◽  
Vol 207 (1) ◽  
pp. 161-180 ◽  
Author(s):  
Horst W. Hamacher ◽  
Stephanie Heller ◽  
Benjamin Rupp
Keyword(s):  
Network Flows ◽  
Dynamic Network ◽  
Evacuation Planning ◽  
Location Models ◽  
Dynamic Network Flows

Dynamic network flows with arc changes

Networks ◽  
1974 ◽  
Vol 4 (3) ◽  
pp. 255-265 ◽  
Author(s):  
E. Minieka
Keyword(s):  
Network Flows ◽  
Dynamic Network ◽  
Dynamic Network Flows

scholarly journals A Trial-and-Error Congestion Pricing Method for Day-to-Day Dynamic Network Flows considering Travelers’ Heterogeneous Inertia Patterns

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Bojian Zhou ◽  
Min Xu ◽  
Yong Zhang
Keyword(s):  
Network Flows ◽  
Congestion Pricing ◽  
Route Choice ◽  
Dynamic Network ◽  
User Equilibrium ◽  
Point Of View ◽  
Trial And Error ◽  
Route Choice Behavior ◽  
Dynamic Network Flows ◽  
Implementation Time

This study proposes a trial-and-error congestion pricing method to achieve system optimum under day-to-day flow dynamics with unknown demand. Travelers are assumed to adjust their route choice day by day so that the resultant traffic flow under a trial of tolls evolves from one day to another. We rigorously demonstrate that if psychological inertia is considered in travelers’ day-to-day route choice behavior, the convergence of the proposed trial-and-error congestion pricing method can be guaranteed without requiring the observed network flows to be in user equilibrium. Furthermore, the proposed method also allows tolls to be updated at irregular time intervals, which greatly relaxes the implementation requirements of existing congestion pricing schemes in the literature. This study is very significant from a practical point of view because it provides a flexibility approach that greatly reduces the implementation time of the traditional trial-and-error congestion pricing method. Numerical experiments are conducted to validate our theoretical findings.

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