Neurolkh: Combining deep learning model with lin-kernighan-helsgaun heuristic for solving the traveling salesman problem
We present NeuroLKH, a novel algorithm that combines deep learning with the strong
traditional heuristic Lin-Kernighan-Helsgaun (LKH) for solving Traveling Salesman Problem …
traditional heuristic Lin-Kernighan-Helsgaun (LKH) for solving Traveling Salesman Problem …
Unsupervised learning for solving the travelling salesman problem
Y Min, Y Bai, CP Gomes - Advances in Neural Information …, 2024 - proceedings.neurips.cc
We propose UTSP, an Unsupervised Learning (UL) framework for solving the Travelling
Salesman Problem (TSP). We train a Graph Neural Network (GNN) using a surrogate loss …
Salesman Problem (TSP). We train a Graph Neural Network (GNN) using a surrogate loss …
Reinforced Lin–Kernighan–Helsgaun algorithms for the traveling salesman problems
Abstract The Traveling Salesman Problem (TSP) is a classical NP-hard combinatorial
optimization problem with many practical variants. The Lin–Kernighan–Helsgaun (LKH) …
optimization problem with many practical variants. The Lin–Kernighan–Helsgaun (LKH) …
Graph neural network guided local search for the traveling salesperson problem
Solutions to the Traveling Salesperson Problem (TSP) have practical applications to
processes in transportation, logistics, and automation, yet must be computed with minimal …
processes in transportation, logistics, and automation, yet must be computed with minimal …
H-tsp: Hierarchically solving the large-scale traveling salesman problem
We propose an end-to-end learning framework based on hierarchical reinforcement
learning, called H-TSP, for addressing the large-scale Traveling Salesman Problem (TSP) …
learning, called H-TSP, for addressing the large-scale Traveling Salesman Problem (TSP) …
Learning 2-opt heuristics for routing problems via deep reinforcement learning
Recent works using deep learning to solve routing problems such as the traveling salesman
problem (TSP) have focused on learning construction heuristics. Such approaches find good …
problem (TSP) have focused on learning construction heuristics. Such approaches find good …
Pointerformer: Deep reinforced multi-pointer transformer for the traveling salesman problem
Abstract Traveling Salesman Problem (TSP), as a classic routing optimization problem
originally arising in the domain of transportation and logistics, has become a critical task in …
originally arising in the domain of transportation and logistics, has become a critical task in …
Memory-efficient transformer-based network model for traveling salesman problem
Combinatorial optimization problems such as Traveling Salesman Problem (TSP) have a
wide range of real-world applications in transportation, logistics, manufacturing. It has …
wide range of real-world applications in transportation, logistics, manufacturing. It has …
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. It has driven the discovery of several …
problem, starting with von Neumann in 1951. It has driven the discovery of several …
Learning to search feasible and infeasible regions of routing problems with flexible neural k-opt
In this paper, we present Neural k-Opt (NeuOpt), a novel learning-to-search (L2S) solver for
routing problems. It learns to perform flexible k-opt exchanges based on a tailored action …
routing problems. It learns to perform flexible k-opt exchanges based on a tailored action …