On the Approximability of Train Routing and the Min-Max Disjoint Paths Problem

TL;DR

This paper models train routing with fixed headways, reduces the problem to min-max disjoint paths, and provides approximation algorithms with guarantees for specific graph classes.

Contribution

It introduces a convoy-based model for train routing, linking it to min-max disjoint paths and analyzing approximation approaches for series-parallel graphs.

Findings

Optimal train routes form convoys, simplifying the problem.

Greedy algorithms achieve logarithmic approximation on series-parallel graphs.

Inapproximability results transfer from min-max disjoint paths to directed acyclic graphs.

Abstract

In train routing, the headway is the minimum distance that must be maintained between successive trains for safety and robustness. We introduce a model for train routing that requires a fixed headway to be maintained between trains, and study the problem of minimizing the makespan, i.e., the arrival time of the last train, in a single-source single-sink network. For this problem, we first show that there exists an optimal solution where trains move in convoys, that is, the optimal paths for any two trains are either the same or are arc-disjoint. Via this insight, we are able to reduce the approximability of our train routing problem to that of the min-max disjoint paths problem, which asks for a collection of disjoint paths where the maximum length of any path in the collection is as small as possible. While min-max disjoint paths inherits a strong inapproximability result on directed acyclic graphs from the multi-level bottleneck assignment problem, we show that a natural greedy composition approach yields a logarithmic approximation in the number of disjoint paths for series-parallel graphs. We also present an alternative analysis of this approach that yields a guarantee depending on how often the decomposition tree of the series-parallel graph alternates between series and parallel compositions on any root-leaf path.