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Combinatorial optimization problems are typically NP-hard, and thus very challenging to solve. In this paper, we present the random key cuckoo search (RKCS) algorithm for solving the famous Travelling Salesman Problem (TSP). We used a…

Neural and Evolutionary Computing · Computer Science 2016-07-18 Aziz Ouaarab , B. Ahiod , Xin-She Yang

Most neural solvers for the Traveling Salesperson Problem (TSP) are trained to output a single solution, even though practitioners rarely stop there: at test time, they routinely spend extra compute on sampling or post-hoc search. This…

Machine Learning · Computer Science 2026-05-04 Andoni Irazusta Garmendia

We consider two algorithmic problems concerning sub-semigroups of Heisenberg groups and, more generally, two-step nilpotent groups. The first problem is Intersection Emptiness, which asks whether a finite number of given finitely generated…

Group Theory · Mathematics 2022-10-28 Ruiwen Dong

In this work, we consider the low rank decomposition (SDPR) of general convex semidefinite programming problems (SDP) that contain both a positive semidefinite matrix and a nonnegative vector as variables. We develop a rank-support-adaptive…

Optimization and Control · Mathematics 2023-12-14 Tianyun Tang , Kim-Chuan Toh

In the Bounded Multiple Traveling Salesman Problem (BMTSP), a tour for each salesman, that starts and ends at the depot and that respects the bounds on the number of cities that a feasible salesman tour should satisfy, is to be constructed.…

Discrete Mathematics · Computer Science 2024-05-30 Víctor Pacheco-Valencia , Nodari Vakhania

The Deligne-Simpson problem (DSP) (resp. the weak DSP) is formulated like this: {\em give necessary and sufficient conditions for the choice of the conjugacy classes $C_j\subset GL(n,{\bf C})$ or $c_j\subset gl(n,{\bf C})$ so that there…

Algebraic Geometry · Mathematics 2007-05-23 Vladimir Petrov Kostov

Tabular Prior-Data Fitted Network (TabPFN) is a foundation model designed for small to medium-sized tabular data, which has attracted much attention recently. This paper investigates the application of TabPFN in Combinatorial Optimization…

Machine Learning · Computer Science 2025-11-11 Nguyen Gia Hien Vu , Yifan Tang , Rey Lim , Yifan Yang , Hang Ma , Ke Wang , G. Gary Wang

Travelling Salesman Problem (TSP) is one of the unsolved problems in computer science. TSP is NP Hard. Till now the best approximation ratio found for symmetric TSP is three by two by Christofides Algorithm more than forty years ago. There…

Data Structures and Algorithms · Computer Science 2021-04-27 Alok Chauhan , Madhusudan Verma

Severe weather events can cause extensive damage to electrical distribution networks, requiring a multi-day restoration effort. Optimizing the dispatch of repair crews minimizes the severe socio-economic consequences of such events.…

Systems and Control · Electrical Eng. & Systems 2025-05-09 Ran Wei , Arindam K. Das , Payman Arabshahi , Daniel S. Kirschen

For some weighted $NP$-complete problems, checking whether a proposed solution is optimal is a non-trivial task. Such is the case for the celebrated traveling salesman problem, or the spin-glass problem in 3 dimensions. In this letter, we…

Statistical Mechanics · Physics 2007-05-23 Henri Orland , Michel Bauer

The Travelling Salesman Problem (TSP) is a well known and challenging combinatorial optimisation problem. Its computational intractability has attracted a number of heuristic approaches to generate satisfactory, if not optimal, candidate…

Emerging Technologies · Computer Science 2013-03-27 Jeff Jones , Andrew Adamatzky

We first show that the Traveling Salesman Problem in an n-vertex graph with average degree bounded by d can be solved in O*(2^{(1-\eps_d)n}) time and exponential space for a constant \eps_d depending only on d, where the O*-notation…

Data Structures and Algorithms · Computer Science 2013-02-18 Marek Cygan , Marcin Pilipczuk

We are given a set of points $p_1,\ldots , p_n$ and a symmetric distance matrix $(d_{ij})$ giving the distance between $p_i$ and $p_j$. We wish to construct a tour that minimizes $\sum_{i=1}^n \ell(i)$, where $\ell(i)$ is the {\em latency}…

In the Many-visits Path TSP, we are given a set of $n$ cities along with their pairwise distances (or cost) $c(uv)$, and moreover each city $v$ comes with an associated positive integer request $r(v)$. The goal is to find a minimum-cost…

Discrete Mathematics · Computer Science 2020-07-23 Kristóf Bérczi , Matthias Mnich , Roland Vincze

Enumeration of all combinatorial types of point configurations and polytopes is a fundamental problem in combinatorial geometry. Although many studies have been done, most of them are for 2-dimensional and non-degenerate cases. Finschi and…

Combinatorics · Mathematics 2012-09-26 Komei Fukuda , Hiroyuki Miyata , Sonoko Moriyama

Robotic systems often require a team of robots to collectively visit multiple targets while optimizing competing objectives, such as total travel cost and makespan. This setting can be formulated as the Multi-Objective Multiple Traveling…

Robotics · Computer Science 2026-03-20 Fengxiaoxiao Li , Xiao Mao , Mingfeng Fan , Yifeng Zhang , Yi Li , Tanishq Duhan , Guillaume Sartoretti

We revisit the problem of finding optimal strategies for deterministic Markov Decision Processes (DMDPs), and a closely related problem of testing feasibility of systems of $m$ linear inequalities on $n$ real variables with at most two…

Data Structures and Algorithms · Computer Science 2021-10-29 Adam Karczmarz

Generalizing work of K\"unnemann, Paturi, and Schneider [ICALP 2017], we study a wide class of high-dimensional dynamic programming (DP) problems in which one must find the shortest path between two points in a high-dimensional grid given a…

Computational Complexity · Computer Science 2024-01-03 Josh Alman , Ethan Turok , Hantao Yu , Hengzhi Zhang

Generalized traveling salesman problem (GTSP) is an extension of classical traveling salesman problem (TSP), which is a combinatorial optimization problem and an NP-hard problem. In this paper, an efficient discrete state transition…

Optimization and Control · Mathematics 2015-09-22 Xiaolin Tang , Chunhua Yang , Xiaojun Zhou , Weihua Gui

Machine Learning (ML) can help solve combinatorial optimization (CO) problems better. A popular approach is to use a neural net to compute on the parameters of a given CO problem and extract useful information that guides the search for…

Machine Learning · Computer Science 2021-10-27 Yeong-Dae Kwon , Jinho Choo , Iljoo Yoon , Minah Park , Duwon Park , Youngjune Gwon