Network flows over time form a fascinating area of research. They model the temporal dynamics of network flow problems occurring in a wide variety of applications. Research in this area has been pursued in two different and mainly independent directions with respect to time modeling: discrete and continuous time models. In this paper we deploy measure theory in order to introduce a general model of network flows over time combining both discrete and continuous aspects into a single model. Here, the flow on each arc is modeled as a Borel measure on the real line (time axis) which assigns to each suitable subset a real value, interpreted as the amount of flow entering the arc over the subset. We focus on the maximum flow problem formulated in...
Flows over time (also called dynamic flows) generalize standard network flows by introducing an elem...
The thesis discusses discrete-time dynamic flows over a finite time horizon T. These flows take time...
We introduce temporal flows on temporal networks. We show that one can find the maximum amount of fl...
Temporal dynamics is a crucial feature of network flow problems occurring in many practical applicat...
AbstractFlow variation over time is an important feature in network flow problems arising in various...
Flow variation over time is an important feature in network flow problems arising in various applica...
More than forty years ago, Ford and Fulkerson studied maximum s-t-flows over time (also called `dyna...
Flow variation over time is an important feature in network flow problems arising in various applica...
Flows over time (also called dynamic flows) generalize standard network flows by introducing an elem...
Flow variation over time is an important feature in network flow problems arising in various applica...
Motivated by applications in road traffic control, we study flows in networks featuring special char...
Abstract. Flows over time (also called dynamic flows) generalize standard network flows by introduci...
111 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.The main problem studied in t...
We introduce temporal flows on temporal networks [17, 19], i.e., networks the links of which exist o...
We introduce temporal flows on temporal networks. We show that one can find the maximum amount of fl...
Flows over time (also called dynamic flows) generalize standard network flows by introducing an elem...
The thesis discusses discrete-time dynamic flows over a finite time horizon T. These flows take time...
We introduce temporal flows on temporal networks. We show that one can find the maximum amount of fl...
Temporal dynamics is a crucial feature of network flow problems occurring in many practical applicat...
AbstractFlow variation over time is an important feature in network flow problems arising in various...
Flow variation over time is an important feature in network flow problems arising in various applica...
More than forty years ago, Ford and Fulkerson studied maximum s-t-flows over time (also called `dyna...
Flow variation over time is an important feature in network flow problems arising in various applica...
Flows over time (also called dynamic flows) generalize standard network flows by introducing an elem...
Flow variation over time is an important feature in network flow problems arising in various applica...
Motivated by applications in road traffic control, we study flows in networks featuring special char...
Abstract. Flows over time (also called dynamic flows) generalize standard network flows by introduci...
111 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.The main problem studied in t...
We introduce temporal flows on temporal networks [17, 19], i.e., networks the links of which exist o...
We introduce temporal flows on temporal networks. We show that one can find the maximum amount of fl...
Flows over time (also called dynamic flows) generalize standard network flows by introducing an elem...
The thesis discusses discrete-time dynamic flows over a finite time horizon T. These flows take time...
We introduce temporal flows on temporal networks. We show that one can find the maximum amount of fl...