Dynamic graph conv-LSTM model with dynamic positional encoding for the large-scale traveling salesman problem
From MaRDI portal
Publication:2688704
DOI10.3934/mbe.2022452OpenAlexW4285246637MaRDI QIDQ2688704
Publication date: 5 March 2023
Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/mbe.2022452
traveling salesman problemlearning heuristicsdeep reinforcement learningdynamic graph Conv-LSTM modeldynamic positional encoding
Uses Software
Cites Work
- Certification of an optimal TSP tour through 85,900 cities
- ``Neural computation of decisions in optimization problems
- The Euclidean traveling salesman problem is NP-complete
- Simple statistical gradient-following algorithms for connectionist reinforcement learning
- Machine learning for combinatorial optimization: a methodological tour d'horizon
- Solving the TSP by the AALHNN algorithm
- Learning the travelling salesperson problem requires rethinking generalization
- Deep policy dynamic programming for vehicle routing problems
- Dynamic Programming Treatment of the Travelling Salesman Problem
- TSPLIB—A Traveling Salesman Problem Library
- The Traveling Salesman Problem: A Survey
This page was built for publication: Dynamic graph conv-LSTM model with dynamic positional encoding for the large-scale traveling salesman problem
