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Found 3 papers, 1 papers with code
Moco: A Learnable Meta Optimizer for Combinatorial Optimization
Our approach, Moco, learns a graph neural network that updates the solution construction procedure based on features extracted from the current search state.
Routing Arena: A Benchmark Suite for Neural Routing Solvers
Neural Combinatorial Optimization has been researched actively in the last eight years.
RP-DQN: An application of Q-Learning to Vehicle Routing Problems
In this paper we present a new approach to tackle complex routing problems with an improved state representation that utilizes the model complexity better than previous methods.
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