Regarding the study of the time-dependent green vehicle path problem (TDGVRP), most of the literature uses the step function to represent the vehicle speed change in order to reduce the computation, ignoring the continuity of vehicle speed, which leads to the lack of accurate carbon emissions measurement. This study represents the vehicle speed variation as a continuous function to make the constructed model more consistent with the actual situation, in order to promote the reduction of carbon emissions generated in the logistics and distribution process, improve the greenhouse effect and ecological environment, and ultimately promote sustainable development. In this paper, a simulated annealing-genetic hybrid algorithm (GA-SA) is proposed to solve the constructed optimization model, and two sets of comparison experiments are designed. The experimental results show that compared with the two classical algorithms, the simulated annealing-genetic hybrid algorithm (GA-SA) has better solution performance, inherits the robustness and potential parallelism of the genetic algorithm, and has a higher practical value. Meanwhile, although the total driving distance of the vehicle path considering carbon emissions increases by 3.52 km, the carbon emission cost and the total cost decrease by 5.6% and 3.4%, respectively, which confirms that the path optimization model considering carbon emissions constructed in this study can not only play the role of restraining carbon emissions but also reduce the total distribution cost and the waste of resources. In this study, a continuous function is used to represent the vehicle speed variation, and two classical optimization algorithms (the genetic algorithm and simulated annealing algorithm) are combined and parameter-optimized, and certain innovations are made in the processing of vehicle speed and the solution algorithm. Finally, the effectiveness of the model and algorithm is verified by experiments.

The Belt and Road Initiative puts higher requirements for the logistics industry. As one of the most energy-consuming industries, logistics is a high-carbon emission industry. Its impact on the environment cannot be ignored. In this context, how to respond to the “Belt and Road” under the concept of sustainable development, to promote the logistics industry to achieve “low consumption, low emissions, high efficiency” of regional sustainability, has become the most important development of China’s logistics industry. Therefore, based on previous research, this paper establishes an input–output index system and uses the SBM-DEA model and Malmquist index model to analyze the efficiency of low-carbon logistics in 17 provinces from 2006 to 2020, explore the overall level of the logistics and the factors affecting efficiency, and compare the efficiency in different periods and regions. Then, through the Tobit regression model, the four main factors affecting the efficiency of the logistics industry are analyzed. The results show that: (1) The highest value of low-carbon logistics efficiency of each province is 1.0000, and the lowest value is only 0.0944. The difference in logistics efficiency values among provinces is large, so there is great room for improvement and development potential. (2) From 2006 to 2020, the low-carbon logistics efficiency of the regions showed an overall upward trend, and the MI index values of each province reached or approached the DEA effective state. Among them, technological progress has a promoting effect, while scale and pure technical efficiency have hindered the efficiency growth. (3) Economic growth and industry structure have a positive effect, while energy consumption and government expenditure are negatively correlated with efficiency.

In this paper, a multisensor data acquisition system based on FPGA is designed to provide an overview of the current development of the company based on the theoretical knowledge of enterprise development strategy. Through a comprehensive investigation of the company’s internal environment, the advantages and disadvantages of the company at this stage are clarified, and the opportunities and threats to the company’s development are analyzed in the context of the external macroenvironment and industry development. The coupling coordination degree from 2011 to 2025 was measured using the coupling coordination degree model based on the original data and the prediction results, and the results showed that from 2011 to 2025, the coupling coordination degree of Hebei Province showed a continuous growth and experienced the transition from low coordination, basic coordination, to medium coordination in the coupling coordination stage, aiming at the most innovative fields, mastering the most advanced technologies, cooperating with industry giants, innovating, and building digital ecology, creating, and forming core competitiveness based on core independent products and platform-based solutions, and further promoting transformation and upgrading and high-quality development. In this paper, the data acquisition system is tested by building an experimental platform. The main purpose is to test the stability and accuracy of each module of the data acquisition system. After each module test of the system meets the design requirements, the parallel mechanism attitude transformation test experiment is completed, including the moving platform moving test experiment and the moving platform rotation test experiment. The experimental results show that the designed data acquisition system has stable program and reliable function.