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In this paper we discuss the application of Artificial Intelligence (AI) to the exemplary industrial use case of the two-dimensional commissioning problem in a high-bay storage, which essentially can be phrased as an instance of Traveling…

Neural and Evolutionary Computing · Computer Science 2024-04-16 Stefan Wintersteller , Martin Uray , Michael Lehenauer , Stefan Huber

We present approximation algorithms for almost all variants of the multi-criteria traveling salesman problem (TSP). First, we devise randomized approximation algorithms for multi-criteria maximum traveling salesman problems (Max-TSP). For…

Data Structures and Algorithms · Computer Science 2011-07-14 Bodo Manthey

Grover's search algorithm is one of the basic building block in the world of quantum algorithms. Successfully applying it to combinatorial optimization problems is a subtle challenge. As a quadratic speedup is not enough to naively search…

For NP-hard combinatorial optimization problems, it is usually difficult to find high-quality solutions in polynomial time. The design of either an exact algorithm or an approximate algorithm for these problems often requires significantly…

Machine Learning · Computer Science 2021-05-07 Kun Lei , Peng Guo , Yi Wang , Xiao Wu , Wenchao Zhao

The generalized traveling salesman problem (GTSP) is an extension of the well-known traveling salesman problem. In GTSP, we are given a partition of cities into groups and we are required to find a minimum length tour that includes exactly…

Data Structures and Algorithms · Computer Science 2010-03-30 Gregory Gutin , Daniel Karapetyan

With applications to many disciplines, the traveling salesman problem (TSP) is a classical computer science optimization problem with applications to industrial engineering, theoretical computer science, bioinformatics, and several other…

Artificial Intelligence · Computer Science 2017-05-26 Yihui He , Ming Xiang

The traveling salesman (or salesperson) problem, short TSP, is a problem of strong interest to many researchers from mathematics, economics, and computer science. Manifold TSP variants occur in nearly every scientific field and application…

Data Structures and Algorithms · Computer Science 2025-11-10 Sophia Saller , Jana Koehler , Andreas Karrenbauer

The Multiple Traveling Salesman Problem (MTSP) extends the traveling salesman problem by assigning multiple salesmen to visit a set of targets from a common depot, with each target visited exactly once while minimizing total tour length. A…

Optimization and Control · Mathematics 2026-04-28 Abhay Singh Bhadoriya , Deepjyoti Deka , Kaarthik Sundar

We develop a general framework for MAP estimation in discrete and Gaussian graphical models using Lagrangian relaxation techniques. The key idea is to reformulate an intractable estimation problem as one defined on a more tractable graph,…

Artificial Intelligence · Computer Science 2007-10-02 Jason K. Johnson , Dmitry M. Malioutov , Alan S. Willsky

We consider a new semidefinite programming (SDP) relaxation of the symmetric traveling salesman problem (TSP) that may be obtained via an SDP relaxation of the more general quadratic assignment problem (QAP). We show that the new relaxation…

Optimization and Control · Mathematics 2009-02-12 Etienne de Klerk , Dmitrii V. Pasechnik , Renata Sotirov

This paper considers multi-goal motion planning in unstructured, obstacle-rich environments where a robot is required to reach multiple regions while avoiding collisions. The planned motions must also satisfy the differential constraints…

Robotics · Computer Science 2025-03-27 Yuanjie Lu , Erion Plaku

The Trigger Arc Traveling Salesman Problem (TA-TSP) extends the classical TSP by introducing dynamic arc costs that change when specific "trigger" arcs are traversed, modeling scenarios such as warehouse operations with compactable storage…

Artificial Intelligence · Computer Science 2025-10-08 Joan Salvà Soler , Grégoire de Lambertye

This paper introduces a new learning-based approach for approximately solving the Travelling Salesman Problem on 2D Euclidean graphs. We use deep Graph Convolutional Networks to build efficient TSP graph representations and output tours in…

Machine Learning · Computer Science 2019-10-15 Chaitanya K. Joshi , Thomas Laurent , Xavier Bresson

We consider the time-dependent traveling salesman problem (TDTSP), a generalization of the asymmetric traveling salesman problem (ATSP) to incorporate time-dependent cost functions. In our model, the costs of an arc can change arbitrarily…

Optimization and Control · Mathematics 2018-05-04 Christoph Hansknecht , Imke Joormann , Sebastian Stiller

We present a new approach for gluing tours over certain tight, 3-edge cuts. Gluing over 3-edge cuts has been used in algorithms for finding Hamilton cycles in special graph classes and in proving bounds for 2-edge-connected subgraph…

Data Structures and Algorithms · Computer Science 2022-03-29 Arash Haddadan , Alantha Newman

The Traveling Salesman Problem is one of the best studied NP-hard problems in combinatorial optimization. Powerful methods have been developed over the last 60 years to find optimum solutions to large TSP instances. The largest TSP instance…

Discrete Mathematics · Computer Science 2014-03-03 Stefan Hougardy , Rasmus T. Schroeder

We revisit the traveling salesman problem with neighborhoods (TSPN) and propose several new approximation algorithms. These constitute either first approximations (for hyperplanes, lines, and balls in $\mathbb{R}^d$, for $d\geq 3$) or…

Computational Geometry · Computer Science 2015-11-26 Adrian Dumitrescu , Csaba D. Tóth

We study the edge-length polytope, motivated both by algorithmic research on the Circulant Traveling Salesman Problem (Circulant TSP) and number-theoretic research related to the Buratti-Horak-Rosa conjecture. Circulant TSP is a special…

Discrete Mathematics · Computer Science 2025-06-13 Samuel C. Gutekunst

We present an application of the tensor network generator-enhanced optimization (TN-GEO) framework to address the traveling salesman problem (TSP), a fundamental combinatorial optimization challenge. Our approach employs a tensor network…

Machine Learning · Computer Science 2026-02-25 Ryo Sakai , Chen-Yu Liu

Combinatorial optimization (CO) problems arise across a broad spectrum of domains, including medicine, logistics, and manufacturing. While exact solutions are often computationally infeasible, many practical applications require…

Machine Learning · Computer Science 2025-05-27 Arman Mielke , Uwe Bauknecht , Thilo Strauss , Mathias Niepert
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