The Asymmetric Travelling Salesman Problem in Sparse Digraphs
{\L}ukasz Kowalik, Konrad Majewski

TL;DR
This paper advances algorithms for the asymmetric traveling salesman problem in sparse digraphs, providing new upper bounds and deterministic algorithms with improved running times for graphs with bounded average outdegree.
Contribution
It introduces novel deterministic algorithms for ATSP in sparse digraphs with improved running times and analyzes known approaches for related problems in sparse graphs.
Findings
Deterministic algorithms with running times O(2^{0.441(d-1)n}) and O^*(τ(d)^{n/2}) for ATSP.
Upper bounds for ATSP in specific sparse digraph classes, e.g., O^*(2^{n/3}) for out- and indegree ≤ 2.
Directed Hamiltonicity solvable in randomized time O^*((2-2^{-d})^n).
Abstract
Asymmetric Travelling Salesman Problem (ATSP) and its special case Directed Hamiltonicity are among the most fundamental problems in computer science. The dynamic programming algorithm running in time developed almost 60 years ago by Bellman, Held and Karp, is still the state of the art for both of these problems. In this work we focus on sparse digraphs. First, we recall known approaches for Undirected Hamiltonicity and TSP in sparse graphs and we analyse their consequences for Directed Hamiltonicity and ATSP in sparse digraphs, either by adapting the algorithm, or by using reductions. In this way, we get a number of running time upper bounds for a few classes of sparse digraphs, including for digraphs with both out- and indegree bounded by 2, and for digraphs with outdegree bounded by 3. Our main results are focused on digraphs of bounded…
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