In a dynamic network, the quickest path problem asks for a path such that a given amount of flow can be sent from source to sink in minimal time. In practical settings, the problem parameters may not be known exactly a-priori. It is therefore of interest to consider robust versions of these problems in which travel times and/or capacities of arcs depend on a certain scenario. This article describes an algorithm for the online min-max quickest path problem which does not rely on any knowledge of the future scenarios but whose performance is competitive to an optimal offline algorithm that has complete knowledge of the scenario sequence in advance. In Gas pipeline systems as dynamic networks, the capacities of arcs are depended to temperature in different days as scenarios. So, investigated strategy can support these systems efficiently.
