We investigate the computational complexity of finding temporally disjoint paths or walks in temporal graphs. There, the edge set changes over discrete time steps and a temporal path (resp. walk) uses edges that appear at monotonically increasing time steps. Two paths (or walks) are temporally disjoint if they never use the same vertex at the same time; otherwise, they interfere. This reflects applications in robotics, traffic routing, or finding safe pathways in dynamically changing networks. On the one extreme, we show that on general graphs the problem is computationally hard. The "walk version" is W[1]-hard when parameterized by the number of routes. However, it is polynomial-time solvable for any constant number of walks. The "path version" remains NP-hard even if we want to find only two temporally disjoint paths. On the other extreme, restricting the input temporal graph to have a path as underlying graph, quite counterintuitively, we find NP-hardness in general but also identify natural tractable cases.
翻译:我们在时间图中调查寻找时间脱节路径或行走在时间图中的计算复杂性。 在那里, 边缘在离散时间步骤和时间路径上设定了变化( 重复行走), 使用的是单声道增加时间步骤的边缘。 两个路径( 或行走) 如果它们从未同时使用同一个顶点, 则暂时脱节; 否则, 它们会干扰。 这反映了在机器人、 交通路线或动态变化网络中找到安全路径的应用。 在一个极端上, 我们在一般图表中显示问题是在计算上很困难的。 “ 行走版本” 以路径数参数化为参数时是W[ 1] 硬的。 然而, 对任何常态行走数来说, 它都是多音调时间可溶的。 “ 路径” 即使我们只想要找到两个暂时脱节路径, 也仍然很硬。 在另一个极端上, 限制输入的时间图有作为底图的路径, 非常直截然, 我们发现在一般的路径中发现 NP- 硬性, 但也识别自然可移动的案例 。