In the Euclidean travelling salesman problem (Euclidean TSP), a salesman must visit $n$ points in Euclidean space, while minimizing the travel distance, according to the Euclidean distance function. In online Euclidean TSP, introduced by Abrahamsen, Bercea, Beretta, Klausen and Kozma [ESA 2024], the points are revealed one at a time, and a time slot must be assigned before the next is revealed. Once a point is assigned to a time slot, it can never be reassigned to another time slot. There are $n$ time slots. Euclidean online TSP is a high-dimensional generalization of online sorting, introduced by Aamand, Abrahamsen, Beretta and Kleist [SODA 2023]. Bertram [ESA 2025] showed an algorithm that achieves a competitive ratio of $O(\sqrt{n})$ in the worst case. In stochastic online Euclidean TSP, the points are sampled uniformly and independently in the unit $d$-cube. Kalavas, Platanos and Tolias [STACS 2026] presented an algorithm achieving a competitive ratio of $O(\log^2 n)$ with high probability for stochastic online Euclidean TSP.
We present a simple algorithm that for $d \geq 2$ achieves an expected competitive ratio of $O(1)$, and for $d=1$ achieves an expected competitive ratio of $O(\log n)$, matching the lower bound by Hu [SODA 2026] for $d=1$. The algorithm is deterministic, and the expectation is due to the stochastic input. We also show that in the variant where there are more time slots than points, i.e., $\left\lceil(1 + \varepsilon)n\right\rceil$ time slots and $d=1$, our algorithm achieves an expected competitive ratio of $O\left(1 + \log \varepsilon^{-1}\right)$. We also survey algorithms from the literature.
We experimentally evaluate our algorithm, which reveals that in all variants the constant factor hidden asymptotically is small. We also evaluate the algorithms from the literature.
We present a polynomial-time approximation scheme (PTAS) for the min-max multiple TSP problem in Euclidean space, where multiple traveling salesmen are tasked with visiting a set of $n$ points and the objective is to minimize the maximum tour length. For an arbitrary $\varepsilon > 0$, our PTAS achieves a $(1 + \varepsilon)$-approximation in time $O \big(n ((1/\varepsilon) \log (n/\varepsilon))^{O(1/\varepsilon)} \big)$. Our approach extends Sanjeev Arora's dynamic-programming (DP) PTAS for the Euclidean TSP (https://doi.org/10.1145/290179.290180). Our algorithm introduces a rounding process t…
A long standing conjecture says that the integrality ratio of the subtour LP for metric TSP is $4/3$. A well known family of graphic TSP instances achieves this lower bound asymptotically. For Euclidean TSP the best known lower bound on the integrality ratio was $8/7$. We improve this value by presenting a family of Euclidean TSP instances for which the integrality ratio of the subtour LP converges to 4/3.
Given a set of $n$ points in the Euclidean plane, such that just $k$ points are strictly inside the convex hull of the whole set, we want to find the shortest tour visiting every point. The fastest known algorithm for the version when $k$ is significantly smaller than $n$, i.e., when there are just few inner points, works in $O(k^{11\sqrt{k}} k^{1.5} n^{3})$ time [Knauer and Spillner, WG 2006], but also requires space of order $k^{c\sqrt{k}}n^{2}$. The best linear space algorithm takes $O(k! k n)$ time [Deineko, Hoffmann, Okamoto, Woeginer, Oper. Res. Lett. 34(1), 106-110]. We construct a line…
We prove that even in average case, the Euclidean Traveling Salesman Problem exhibits an integrality gap of $(1+ε)$ for $ε>0$ when the Held-Karp Linear Programming relaxation is augmented by all comb inequalities of bounded size. This implies that large classes of branch-and-cut algorithms take exponential time for the Euclidean TSP, even on random inputs.
In this paper, we consider the Online Traveling Salesperson Problem (OLTSP) where the locations of the requests are known in advance, but not their arrival times. We study both the open variant, in which the algorithm is not required to return to the origin when all the requests are served, as well as the closed variant, in which the algorithm has to return to the origin after serving all the requests. Our aim is to measure the impact of the extra knowledge of the locations on the competitiveness of the problem. We present an online 3/2-competitive algorithm for the general case and a matching…
We study exact algorithms for Euclidean TSP in $\mathbb{R}^d$. In the early 1990s algorithms with $n^{O(\sqrt{n})}$ running time were presented for the planar case, and some years later an algorithm with $n^{O(n^{1-1/d})}$ running time was presented for any $d\geq 2$. Despite significant interest in subexponential exact algorithms over the past decade, there has been no progress on Euclidean TSP, except for a lower bound stating that the problem admits no $2^{O(n^{1-1/d-ε})}$ algorithm unless ETH fails. Up to constant factors in the exponent, we settle the complexity of Euclidean TSP by giving…
In the Traveling Salesperson Problem with Neighborhoods (TSPN), we are given a collection of geometric regions in some space. The goal is to output a tour of minimum length that visits at least one point in each region. Even in the Euclidean plane, TSPN is known to be APX-hard, which gives rise to studying more tractable special cases of the problem. In this paper, we focus on the fundamental special case of regions that are hyperplanes in the $d$-dimensional Euclidean space. This case contrasts the much-better understood case of so-called fat regions. While for $d=2$ an exact algorithm with r…
In the Euclidean TSP with neighborhoods (TSPN), we are given a collection of n regions (neighborhoods) and we seek a shortest tour that visits each region. As a generalization of the classical Euclidean TSP, TSPN is also NP-hard. In this paper, we present new approximation results for the TSPN, including (1) a constant-factor approximation algorithm for the case of arbitrary connected neighborhoods having comparable diameters; and (2) a PTAS for the important special case of disjoint unit disk neighborhoods (or nearly disjoint, nearly-unit disks). Our methods also yield improved approximation …
The question of whether all problems in NP class are also in P class is generally considered one of the most important open questions in mathematics and theoretical computer science as it has far-reaching consequences to other problems in mathematics, computer science, biology, philosophy and cryptography. There are intensive research on proving `NP not equal to P' and `NP equals to P'. However, none of the `proved' results is commonly accepted by the research community up to date. In this paper, motived by approximability of traveling salesman problem (TSP) in polynomial time, we aim to provi…
Institute of Information Science, Academia Sinica（中央研究院资讯科学研究所）；National Tsing Hua University（国立清华大学）；Columbia University（哥伦比亚大学）
We initiate the study of online routing problems with predictions, inspired by recent exciting results in the area of learning-augmented algorithms. A learning-augmented online algorithm which incorporates predictions in a black-box manner to outperform existing algorithms if the predictions are accurate while otherwise maintaining theoretical guarantees even when the predictions are extremely erroneous is a popular framework for overcoming pessimistic worst-case competitive analysis. In this study, we particularly begin investigating the classical online traveling salesman problem (OLTSP), wh…
We study a common delivery problem encountered in nowadays online food-ordering platforms: Customers order dishes online, and the restaurant delivers the food after receiving the order. Specifically, we study a problem where $k$ vehicles of capacity $c$ are serving a set of requests ordering food from one restaurant. After a request arrives, it can be served by a vehicle moving from the restaurant to its delivery location. We are interested in serving all requests while minimizing the maximum flow-time, i.e., the maximum time length a customer waits to receive his/her food after submitting the…
Parameterized runtime analysis seeks to understand the influence of problem structure on algorithmic runtime. In this paper, we contribute to the theoretical understanding of evolutionary algorithms and carry out a parameterized analysis of evolutionary algorithms for the Euclidean traveling salesperson problem (Euclidean TSP). We investigate the structural properties in TSP instances that influence the optimization process of evolutionary algorithms and use this information to bound the runtime of simple evolutionary algorithms. Our analysis studies the runtime in dependence of the number of …
National University of Singapore（新加坡国立大学）；National and Kapodistrian University of Athens（雅典国立卡波迪斯特里安大学）；Max Planck Institut für Informatik（马克斯·普朗克信息学研究所）；Universität des Saarlandes（萨尔大学）
We study the online Traveling Salesman Problem (TSP) on the line augmented with machine-learned predictions. In the classical problem, there is a stream of requests released over time along the real line. The goal is to minimize the makespan of the algorithm. We distinguish between the open variant and the closed one, in which we additionally require the algorithm to return to the origin after serving all requests. The state of the art is a $1.64$-competitive algorithm and a $2.04$-competitive algorithm for the closed and open variants, respectively \cite{Bjelde:1.64}. In both cases, a tight l…
We consider TSP with time windows and service time. In this problem we receive a sequence of requests for a service at nodes in a metric space and a time window for each request. The goal of the online algorithm is to maximize the number of requests served during their time window. The time to traverse an edge is the distance between the incident nodes of that edge. Serving a request requires unit time. We characterize the competitive ratio for each metric space separately. The competitive ratio depends on the relation between the minimum laxity (the minimum length of a time window) and the di…
The Traveling Salesman Problem (TSP) is among the most famous NP-hard optimization problems. We design for this problem a randomized polynomial-time algorithm that computes a (1+eps)-approximation to the optimal tour, for any fixed eps>0, in TSP instances that form an arbitrary metric space with bounded intrinsic dimension. The celebrated results of Arora (A-98) and Mitchell (M-99) prove that the above result holds in the special case of TSP in a fixed-dimensional Euclidean space. Thus, our algorithm demonstrates that the algorithmic tractability of metric TSP depends on the dimensionality of …
2-Opt is probably the most basic local search heuristic for the TSP. This heuristic achieves amazingly good results on real world Euclidean instances both with respect to running time and approximation ratio. There are numerous experimental studies on the performance of 2-Opt. However, the theoretical knowledge about this heuristic is still very limited. Not even its worst case running time on 2-dimensional Euclidean instances was known so far. We clarify this issue by presenting, for every $p\in\mathbb{N}$, a family of $L_p$ instances on which 2-Opt can take an exponential number of steps. Pr…
We consider the rooted orienteering problem in Euclidean space: Given $n$ points $P$ in $\mathbb R^d$, a root point $s\in P$ and a budget $\mathcal B>0$, find a path that starts from $s$, has total length at most $\mathcal B$, and visits as many points of $P$ as possible. This problem is known to be NP-hard, hence we study $(1-δ)$-approximation algorithms. The previous Polynomial-Time Approximation Scheme (PTAS) for this problem, due to Chen and Har-Peled (2008), runs in time $n^{O(d\sqrt{d}/δ)}(\log n)^{(d/δ)^{O(d)}}$, and improving on this time bound was left as an open problem. Our main con…
We give a polynomial time, $(1+ε)$-approximation algorithm for the traveling repairman problem (TRP) in the Euclidean plane and on weighted trees. This improves on the known quasi-polynomial time approximation schemes for these problems. The algorithm is based on a simple technique that reduces the TRP to what we call the \emph{segmented TSP}. Here, we are given numbers $l_1,\dots,l_K$ and $n_1,\dots,n_K$ and we need to find a path that visits at least $n_h$ points within path distance $l_h$ from the starting point for all $h\in\{1,\dots,K\}$. A solution is $α$-approximate if at least $n_h$ po…
For any $ε>0$, Laue and Matijević [CCCG'07, IPL'08] give a PTAS for finding a $(1+ε)$-approximate solution to the $k$-hop MST problem in the Euclidean plane that runs in time $(n/ε)^{O(k/ε)}$. In this paper, we present an algorithm that runs in time $(n/ε)^{O(\log k \cdot(1/ε)^2\cdot\log^2(1/ε))}$. This gives an improvement on the dependency on $k$ on the exponent, while having a worse dependency on $ε$. As in Laue and Matijević, we follow the framework introduced by Arora for Euclidean TSP. Our key ingredients include exponential distance scaling and compression of dynamic programming state t…
We consider a special case of the generalized minimum spanning tree problem (GMST) and the generalized travelling salesman problem (GTSP) where we are given a set of points inside the integer grid (in Euclidean plane) where each grid cell is $1 \times 1$. In the MST version of the problem, the goal is to find a minimum tree that contains exactly one point from each non-empty grid cell (cluster). Similarly, in the TSP version of the problem, the goal is to find a minimum weight cycle containing one point from each non-empty grid cell. We give a $(1+4\sqrt{2}+ε)$ and $(1.5+8\sqrt{2}+ε)$-approxim…
We study the problem of finding a tour of $n$ points in which every edge is long. More precisely, we wish to find a tour that visits every point exactly once, maximizing the length of the shortest edge in the tour. The problem is known as Maximum Scatter TSP, and was introduced by Arkin et al. (SODA 1997), motivated by applications in manufacturing and medical imaging. Arkin et al. gave a $0.5$-approximation for the metric version of the problem and showed that this is the best possible ratio achievable in polynomial time (assuming $P \neq NP$). Arkin et al. raised the question of whether a be…
Learning-Based TSP-Solvers Tend to Be Overly Greedy
Academy of Mathematics and Systems Science, Chinese Academy of Sciences（中国科学院数学与系统科学研究院）；School of Mathematics Sciences, University of Chinese Academy of Sciences（中国科学院大学数学科学学院）
In this paper, we introduce the online service with delay problem. In this problem, there are $n$ points in a metric space that issue service requests over time, and a server that serves these requests. The goal is to minimize the sum of distance traveled by the server and the total delay in serving the requests. This problem models the fundamental tradeoff between batching requests to improve locality and reducing delay to improve response time, that has many applications in operations management, operating systems, logistics, supply chain management, and scheduling. Our main result is to sho…
We consider the online search problem in which a server starting at the origin of a $d$-dimensional Euclidean space has to find an arbitrary hyperplane. The best-possible competitive ratio and the length of the shortest curve from which each point on the $d$-dimensional unit sphere can be seen are within a constant factor of each other. We show that this length is in $Ω(d)\cap O(d^{3/2})$.
The online Dial-a-Ride problem is a fundamental online problem in a metric space, where transportation requests appear over time and may be served in any order by a single server with unit speed. Restricted to the real line, online Dial-a-Ride captures natural problems like controlling a personal elevator. Tight results in terms of competitive ratios are known for the general setting and for online TSP on the line (where source and target of each request coincide). In contrast, online Dial-a-Ride on the line has resisted tight analysis so far, even though it is a very natural online problem. W…
In this paper, we study the online Euclidean spanners problem for points in $\mathbb{R}^d$. Suppose we are given a sequence of $n$ points $(s_1,s_2,\ldots, s_n)$ in $\mathbb{R}^d$, where point $s_i$ is presented in step~$i$ for $i=1,\ldots, n$. The objective of an online algorithm is to maintain a geometric $t$-spanner on $S_i=\{s_1,\ldots, s_i\}$ for each step~$i$. First, we establish a lower bound of $Ω(\varepsilon^{-1}\log n / \log \varepsilon^{-1})$ for the competitive ratio of any online $(1+\varepsilon)$-spanner algorithm, for a sequence of $n$ points in 1-dimension. We show that this bo…
We study online competitive algorithms for the \emph{line chasing problem} in Euclidean spaces $\reals^d$, where the input consists of an initial point $P_0$ and a sequence of lines $X_1,X_2,...,X_m$, revealed one at a time. At each step $t$, when the line $X_t$ is revealed, the algorithm must determine a point $P_t\in X_t$. An online algorithm is called $c$-competitive if for any input sequence the path $P_0, P_1,...,P_m$ it computes has length at most $c$ times the optimum path. The line chasing problem is a variant of a more general convex body chasing problem, where the sets $X_t$ are arbi…
Given a metric space $\mathcal{M}=(X,δ)$, a weighted graph $G$ over $X$ is a metric $t$-spanner of $\mathcal{M}$ if for every $u,v \in X$, $δ(u,v)\le d_G(u,v)\le t\cdot δ(u,v)$, where $d_G$ is the shortest path metric in $G$. In this paper, we construct spanners for finite sets in metric spaces in the online setting. Here, we are given a sequence of points $(s_1, \ldots, s_n)$, where the points are presented one at a time (i.e., after $i$ steps, we saw $S_i = \{s_1, \ldots , s_i\}$). The algorithm is allowed to add edges to the spanner when a new point arrives, however, it is not allowed to re…
Let $\mathcal{F}$ be a family of sets in some metric space. In the $\mathcal{F}$-chasing problem, an online algorithm observes a request sequence of sets in $\mathcal{F}$ and responds (online) by giving a sequence of points in these sets. The movement cost is the distance between consecutive such points. The competitive ratio is the worst case ratio (over request sequences) between the total movement of the online algorithm and the smallest movement one could have achieved by knowing in advance the request sequence. The family $\mathcal{F}$ is said to be chaseable if there exists an online alg…
