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The ATSP polytope can be expressed by asymmetric polynomial size linear program.

Discrete Mathematics · Computer Science 2008-11-10 Sergey Gubin

In this paper we use marker method and propose a new mutation operator that selects the nearest neighbor among all near neighbors solving Traveling Salesman Problem.

Neural and Evolutionary Computing · Computer Science 2013-07-23 Masoumeh Vali

We present a map from the travelling salesman problem (TSP), a prototypical NP-complete combinatorial optimisation task, to the ground state associated with a system of many-qudits. Conventionally, the TSP is cast into a quadratic…

This paper proposes a dual divide-and-optimize algorithm (DualOpt) for solving the large-scale traveling salesman problem (TSP). DualOpt combines two complementary strategies to improve both solution quality and computational efficiency.…

Artificial Intelligence · Computer Science 2025-01-16 Shipei Zhou , Yuandong Ding , Chi Zhang , Zhiguang Cao , Yan Jin

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

This work presents solutions to the Traveling Salesperson Problem with precedence constraints (TSPPC) using Deep Reinforcement Learning (DRL) by adapting recent approaches that work well for regular TSPs. Common to these approaches is the…

Machine Learning · Computer Science 2022-09-20 Christian Löwens , Inaam Ashraf , Alexander Gembus , Genesis Cuizon , Jonas K. Falkner , Lars Schmidt-Thieme

This paper proposes an algorithmic method to heuristically solve the famous Travelling Salesman Problem (TSP) when the salesman's path evolves in continuous state space and discrete time but with otherwise arbitrary (nonlinear) dynamics.…

Optimization and Control · Mathematics 2021-03-02 Alexander Weber , Alexander Knoll

The Covering Salesman Problem (CSP) is a generalization of the Traveling Salesman Problem in which the tour is not required to visit all vertices, as long as all vertices are covered by the tour. The objective of CSP is to find a minimum…

Data Structures and Algorithms · Computer Science 2021-04-05 Lucas Porto Maziero , Fábio Luiz Usberti , Celso Cavellucci

Over the past few years, unmanned aerial vehicles (UAV), also known as drones, have been adopted as part of a new logistic method in the commercial sector called "last-mile delivery". In this novel approach, they are deployed alongside…

Artificial Intelligence · Computer Science 2018-01-03 Quang Minh Ha , Yves Deville , Quang Dung Pham , Minh Hoàng Hà

We provide exact and approximation methods for solving a geometric relaxation of the Traveling Salesman Problem (TSP) that occurs in curve reconstruction: for a given set of vertices in the plane, the problem Minimum Perimeter Polygon (MPP)…

In many real-world settings, problem instances that need to be solved are quite similar, and knowledge from previous optimization runs can potentially be utilized. We explore this for the Traveling Salesperson problem with time windows…

Neural and Evolutionary Computing · Computer Science 2026-04-17 Hy Nguyen , Thanh Nguyen Pham , Helen Yuliana Angmalisang , Liam Wigney , Frank Neumann

This article describes counter example prepared in order to prove that linear formulation of TSP problem proposed in [arXiv:0803.4354] is incorrect (it applies also to QAP problem formulation in [arXiv:0802.4307]). Article refers not only…

Computational Complexity · Computer Science 2008-06-02 Radoslaw Hofman

Recent advancements in solving large-scale traveling salesman problems (TSP) utilize the heatmap-guided Monte Carlo tree search (MCTS) paradigm, where machine learning (ML) models generate heatmaps, indicating the probability distribution…

Artificial Intelligence · Computer Science 2024-06-07 Yifan Xia , Xianliang Yang , Zichuan Liu , Zhihao Liu , Lei Song , Jiang Bian

Combinatorial optimization is the field devoted to the study and practice of algorithms that solve NP-hard problems. As Machine Learning (ML) and deep learning have popularized, several research groups have started to use ML to solve…

Artificial Intelligence · Computer Science 2019-10-01 Antoine François , Quentin Cappart , Louis-Martin Rousseau

We present a trajectory optimization algorithm for the traveling salesman problem (TSP) in graphs of convex sets (GCS). Our framework uses an augmented graph of convex sets to encode the TSP specification and solve it exactly as a shortest…

Systems and Control · Electrical Eng. & Systems 2026-04-09 Gael Luna , Tyler Summers

We study the metric $s$-$t$ path Traveling Salesman Problem (TSP). [An, Kleinberg, and Shmoys, STOC 2012] improved on the long standing $\frac{5}{3}$-approximation factor and presented an algorithm that achieves an approximation factor of…

Data Structures and Algorithms · Computer Science 2015-03-17 Zhihan Gao

We present a successive constraint approach that makes it possible to cheaply solve large-scale linear matrix inequalities for a large number of parameter values. The efficiency of our method is made possible by an offline/online…

Numerical Analysis · Mathematics 2017-08-08 Robert O'Connor

We consider the bicriteria asymmetric travelling salesman problem (bi-ATSP). Optimal solution to a multicriteria problem is usually supposed to be the Pareto set, which is rather wide in real-world problems. For the first time we apply to…

Neural and Evolutionary Computing · Computer Science 2018-12-04 Aleksey O. Zakharov , Yulia V. Kovalenko

The famous Travelling Salesman Problem (TSP) is an important category of optimization problems that is mostly encountered in various areas of science and engineering. Studying optimization problems motivates to develop advanced techniques…

Quantum Physics · Physics 2018-05-29 Karthik Srinivasan , Saipriya Satyajit , Bikash K. Behera , Prasanta K. Panigrahi

The recently presented idea to learn heuristics for combinatorial optimization problems is promising as it can save costly development. However, to push this idea towards practical implementation, we need better models and better ways of…

Machine Learning · Statistics 2019-02-08 Wouter Kool , Herke van Hoof , Max Welling
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