DSApr 30

Temporal Routing in Static Networks: The Schedule Completion Problem

arXiv:2604.2775734.7
Predicted impact top 38% in DS · last 90 daysOriginality Synthesis-oriented
AI Analysis

The work addresses theoretical routing problems relevant to railway scheduling, but the results are primarily theoretical and incremental.

The paper introduces the TemporallyEdgeDisjointScheduleCompletion (TEDSC) problem, which combines temporal edge demands with static rail networks, and provides a polynomial-time algorithm for it. It also analyzes parameterized complexity and approximation for bounded variants.

We introduce the TemporallyEdgeDisjointScheduleCompletion (TEDSC) problem in which we need to cover a set of temporal edge demands $D$ by routing $k$ temporal walks through a directed static graph while remaining temporally edge disjoint. This problem combines the temporal aspects of train routing and passenger demands with the static nature of real-world rail networks. We present a polynomial time algorithm for TEDSC. Motivated by real world constraints, we next investigate two restricted variants of TEDSC in which each walk can only travel for some bounded distance or time $h$. We show that both are tractable when parameterized by $k + h$, but hard for $h$ and $k + |D|$. If we fix the underlying network, the two problems exhibit distinct complexities: The distance variant remains $W[1]$-hard parameterized by $k$ even on a path of three vertices whereas the time variant admits an FPT algorithm on any fixed star. Finally, we show how to approximate the number of required walks up to a factor of $(2-h^{-1})$.

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