Traveling Salesman Problem
67 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Traveling Salesman Problem
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Libraries
Use these libraries to find Traveling Salesman Problem models and implementations
TSP/HCP Benchmark set
Most implemented papers
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization
qcappart/hybrid-cp-rl-solver
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In this work, we propose a general and hybrid approach, based on DRL and CP, for solving combinatorial optimization problems.
Cable Tree Wiring -- Benchmarking Solvers on a Real-World Scheduling Problem with a Variety of Precedence Constraints
We summarize our investigations to model this cable tree wiring Problem (CTW) as a traveling salesman problem with atomic, soft atomic, and disjunctive precedence constraints as well as tour-dependent edge costs such that it can be solved by state-of-the-art constraint programming (CP), Optimization Modulo Theories (OMT), and mixed-integer programming (MIP) solvers.
Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problem
We address the Traveling Salesman Problem (TSP), a famous NP-hard combinatorial optimization problem.
Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instances
Spider-scnu/TSP
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For the traveling salesman problem (TSP), the existing supervised learning based algorithms suffer seriously from the lack of generalization ability.
The Transformer Network for the Traveling Salesman Problem
The Traveling Salesman Problem (TSP) is the most popular and most studied combinatorial problem, starting with von Neumann in 1951.
S$^*$: A Heuristic Information-Based Approximation Framework for Multi-Goal Path Finding
We combine ideas from uni-directional and bi-directional heuristic search, and approximation algorithms for the Traveling Salesman Problem, to develop a novel framework for a Multi-Goal Path Finding (MGPF) problem that provides a 2-approximation guarantee.
Solve routing problems with a residual edge-graph attention neural network
pengguo318/RoutingProblemGANN
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In this paper, an end-to-end deep reinforcement learning framework is proposed to solve this type of combinatorial optimization problems.
Learning Geometric Combinatorial Optimization Problems using Self-attention and Domain Knowledge
In the decoder, a new masking scheme using domain knowledge is proposed to provide a high penalty when the geometric requirement of the problem is not satisfied.
Exact and Heuristic Approaches to Drone Delivery Problems
The Flying Sidekick Traveling Salesman Problem (FSTSP) considers a delivery system composed by a truck and a drone.
A New Constructive Heuristic driven by Machine Learning for the Traveling Salesman Problem
So far, ML were engaged to create CLs and values on the edges of these CLs expressing ML preferences at solution insertion.
