A mathematical model for vehicle path planning(DCVRPTW)was established to optimize the delivery path of agricultural inputs supply chain orders,taking into account constraints such as the comprehensive range,maximum load capacity,and time window of new ener-gy trucks.The model comprehensively optimizes the fixed and transportation costs of vehicles,and proposes a swarm intelligence optimization algorithm framework based on deep reinforcement learning(DRL-SIA).An intelligent agent is a decision-maker who selects the best action from the action pool based on the environmental state as input to change the environment and obtain environmental rewards.The DRL-SIA al-gorithm combines trained agents with swarm intelligence algorithms to replace the original algorithm for decision selection,thereby improving optimization speed and accuracy.The experiment shows that the optimal solution of the proposed algorithm is superior to other algorithms in all cases,verifying that the algorithm can effectively reduce logistics transportation costs in the agricultural material supply chain.
维普
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