A Vehicle-cargo Matching Algorithm Based on Multi-agent Reinforcement Learning
Aiming at the"many-to-many"vehicle-cargo matching problem of network freight enterpri-ses,based on the matching decision-making process,the vehicle-cargo matching problem was modeled as a multi-agent Markov decision-making process.A multi-agent reinforcement learning algorithm based on multi-layer perceptron agent network,fully connected hybrid network and hyperparametric network was used to simulate and optimize the multi-agent Markov decision-making process.Numeri-cal experiments were carried out based on the matching data of real network freight platform and dif-ferent scale transportation network environments.The results show that the proposed algorithm has good performance in solving the large-scale vehicle-cargo matching problem.
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