Abstract
With the improvement of the economic level, people’s quality of life continues to improve, the demand for fresh food is increasing, and the logistics of fresh products is also developing rapidly. We effectively balance the relationship between transportation costs and service levels in fresh product logistics and transportation businesses, improve the transportation capacity and efficiency of logistics transportation businesses, and improve the resource utilization of businesses. It is important for the development of the logistics transportation scheduling industry for fresh products. Significance. Based on this, this paper proposes a DNQ algorithm based on pointer network, which solves the single fresh product distribution service center-regional efficient logistics scheduling problem, and a feasible logistics transportation scheduling scheme can be obtained through simulation experiments. The simulation results show that the algorithm is superior to other common intelligent algorithms in terms of accuracy and stability, which proves that the algorithm is effective and feasible (the research results cannot be directly shown in the abstract and need to be supplemented) At the same time, it further explored the DNQ algorithm to improve the correction network, which can solve the complex problem of multiple fresh product distribution service centers-regional efficient logistics scheduling. It is a successful attempt to improve the solution algorithm. Complex logistics and transportation scheduling problems provide ideas and have good guidance and reference significance.
Highlights
With the further improvement of residents’ living standards, the scale of online and offline demand in the fresh product market has gradually expanded
When using the value function and strategy function of the pointer network model-fitting algorithm proposed in the previous section, it is found that for the efficient logistics transportation scheduling problem of multiple fresh product service centers, after the distribution service center is added, the number of transportation vehicles will increase or decrease at the same time. e input becomes very complicated; the encoder input becomes inefficient, which affects the performance of the algorithm
In order to improve the efficiency of input, this section improves the pointer network model, simplifies its structure, and makes it suitable for solving the efficient logistics transportation scheduling problem of multiple fresh product distribution service centers
Summary
With the further improvement of residents’ living standards, the scale of online and offline demand in the fresh product market has gradually expanded. Sun Zhidan and others used cost-saving methods and human ant colony algorithms to solve the path optimization problem of fresh agricultural products and fresh products logistics distribution [12,13,14]. Ge Changfei et al [15] optimized the existing logistics and transportation model of fresh food products from the perspective of product quality and order quantity. Huang Chunhui’s research [16] focuses on the emergency complementation of intersupplier inventory in the food cold chain and the optimization of the entire fresh product logistics and transportation network. Ghezavati et al [20,21,22] established an optimization model for the supply chain distribution network of fresh agricultural products from the place of production to the customer with the maximum benefit as the objective function and verified the effectiveness of the model. Marco Bortolini and others created a three-objective distribution planning model to optimize the logistics distribution path of fresh products with the minimum cost as the goal [22, 23].In solving the scheduling problem model, Zhang Jianfeng and others used a deep recurrent neural network model embedded with a pointer network to solve the job shop scheduling problem
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