While routing in static networks has become quite easy, routing in dynamic networks turns out to be more
difficult. Public transit networks such as bus and railway are inherently time-dependent. The travel time from one
station to another is not static; it depends on the arrival time of the user at the departure station. Cooke and Halsey
(1966) showed that standard algorithms like Dijkstra could be augmented to cope with the time dependency aspect
of public transportation modes. However, that would be at the expense of additional computational efforts,
especially when the size of the network becomes very important (Delling, 2009). Extensive works have therefore
been investigated to augment speed up techniques used in static networks to accommodate for the new variant of
SPP raised when dealing with time-dependent networks. For more details about accelerating techniques in dynamic
networks, the reader can refer to (Bauer et al., 2011).
While routing in static networks has become quite easy, routing in dynamic networks turns out to be moredifficult. Public transit networks such as bus and railway are inherently time-dependent. The travel time from onestation to another is not static; it depends on the arrival time of the user at the departure station. Cooke and Halsey(1966) showed that standard algorithms like Dijkstra could be augmented to cope with the time dependency aspectof public transportation modes. However, that would be at the expense of additional computational efforts,especially when the size of the network becomes very important (Delling, 2009). Extensive works have thereforebeen investigated to augment speed up techniques used in static networks to accommodate for the new variant ofSPP raised when dealing with time-dependent networks. For more details about accelerating techniques in dynamicnetworks, the reader can refer to (Bauer et al., 2011).
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