Real-time emergency management mode of cold chain logistics for agricultural products under the background of “Internet+”

How to build a cold chain supply chain system for fresh agricultural products through blockchain technology-A study of tripartite evolutionary game theory based on prospect theory

The global cold chain logistics market is witnessing a significant upswing, driven by the rising demand for perishable food products and increasing shipment volumes worldwide. Technological advancements are leading to a more intelligent and digitally enabled cold chain logistics system. However, the high loss rate of fresh agricultural products in China poses a significant threat to the country's food security. Therefore, it is imperative to explore innovative solutions, such as blockchain, to address the challenges of traditional cold chain logistics. In this paper, inspired by the prospect theory and evolutionary game theory, we propose an evolutionary game model to analyze the behavioral strategies of the tripartite of n-level cold chain participants, consumers, and government. Using MATLAB software, the numerical simulation of the game path of this tripartite theory is conducted, and the influence of variable parameters on the evolutionary process and outcomes of the system is analyzed. The results the following: (1) The development of an effective cold chain supply chain system can be divided into three stages, and blockchain technology plays a pivotal role in creating a seamless cold chain environment. The cost of blockchain adoption, government rewards, as well as penalties can significantly influence the behavioral choices of the three stakeholders. (2) The behavior of individual cold chain participants has a strong negative externality, which can impact the behavior of others. We also find that the larger the scale of the cold chain, the lower the probability of default by the participants. (3) The government's adoption of blockchain technology and the implementation of effective incentive policies can foster the successful development of the cold chain blockchain infrastructure. Our research contributes to the theoretical understanding of cold chain logistics decision making and policy creation for the tripartite stakeholders, including cold chain participants, consumers, and government. Our findings can serve as a valuable reference for scientific decision making and policy formulation to encourage the development of a robust cold chain supply chain system.

Optimization Path and Design of Intelligent Logistics Management System Based on ROS Robot

With the rapid development of the Internet of Things (IoT), the logistics and transportation industry is booming. At the same time, with the advancement of AI technology, intelligent logistics is also gradually emerging, and the purpose of intelligent logistics is to use different types of automatic guided transport machines to replace people to handle and move products. At the same time, with the help of big data, cloud computing, artificial intelligence, sensor technology, and other technologies, we can achieve logistics automation. However, the current logistics robot creation platforms are diverse, which makes intelligent logistics robots diverse in variety and wide in application and also makes the creation and use of robots more challenging. Robot Operating System (ROS) is an open-source software platform that supports programming in multiple languages and has excellent adaptability. In addition, most of the currently used path planning focuses on a single target point, which is insufficient to support the current needs of multitasking in intelligent logistics. Therefore, this paper aimed to design an intelligent logistics management system based on ROS robot and proposed to use the A-star algorithm to calculate the shortest path of the robot so as to achieve the optimal path. In the simulation experiment, 20 ROS robots were selected and divided into two groups. In the logistics warehouse of different transportation nodes, 20 ROS robots were set up to transport goods of different weights in the experiment, and the transportation data were collected at last. The final simulation results have shown that the power consumption and response delay performance of the ROS robot are good, and the logistics transportation speed is significantly improved. In addition, compared with the traditional transportation method, the daily transportation weight of each robot is up to 310.1% and the monthly profit is up to 171%, which shows that the intelligent logistics management system designed in this paper is more efficient in logistics and transportation and can bring more profits.