Logistics Center Selection and Logistics Network Construction from the Perspective of Urban Geographic Information Fusion.

The last-mile logistics in cities have become an indispensable part of the urban logistics system. This study aims to explore the effective selection of last-mile logistics nodes to enhance the efficiency of logistics distribution, strengthen the image of corporate distribution, further reduce corporate operating costs, and alleviate urban traffic congestion. This paper proposes a clustering-based approach to identify urban logistics nodes from the perspective of geographic information fusion. This method comprehensively considers several key indicators, including the coverage, balance, and urban traffic conditions of logistics distribution. Additionally, we employed a greedy algorithm to identify secondary nodes around primary nodes, thus constructing an effective nodal network. To verify the practicality of this model, we conducted an empirical simulation study using the logistics demand and traffic conditions in the Xianlin District of Nanjing. This research not only identifies the locations of primary and secondary logistics nodes but also provides a new perspective for constructing urban last-mile logistics systems, enriching the academic research related to the construction of logistics nodes. The results of this study are of significant theoretical and practical importance for optimizing urban logistics networks, enhancing logistics efficiency, and promoting the improvement of urban traffic conditions.

A power allocation strategy for fuel cell ship considering fuel cell performance difference.

This paper focuses on designing a power allocation strategy for a fuel cell ship. The performance of the fuel cell varies during operation, so a power allocation strategy considering fuel cell performance differences is proposed, which consists of two layers. In the first layer, the maximum power and maximum efficiency of each fuel cell system (FCS) are updated in real-time with an online parameter identification model, which is composed of the fuel cell semi-empirical model and adaptive Kalman filter. The second layer takes the state of charge of the battery energy storage system, the maximum power, and the maximum efficiency as inputs for power allocation. Compared with the equal allocation strategy and daisy chain strategy, the total hydrogen consumption reduces by 5.3% and 15.1% and the total output power of the FCS with poor performance reduces by 14.1% and 15.7%. The results show that the proposed method can improve the efficiency of the ship power system and reduce the operational burden of the FCS with poor performance.

The evolution and determinants of Chinese inter-provincial green development efficiency: an MCSE-DEA-Tobit-based perspective.

Continuous and rapid economic development has brought about excessive resource consumption and environmental pollution. Therefore, it is particularly essential to coordinate economic, resource, and environmental factors to achieve sustainable development. This paper develops a new data envelopment analysis (DEA) method that can be used for multi-level complex system evaluation (MCSE-DEA) to reveal the inter-provincial green development efficiency (GDE) in China from 2010 to 2018. Moreover, the Tobit model is applied to explore the influencing factors of GDE. We found that (i) the MCSE-DEA model tends to have lower efficiency scores than the traditional P-DEA (panel data envelopment analysis) model, and the top three provinces are Shanghai, Tianjin, and Fujian; (ii) the efficiency shows an increasing trend during the whole study period. The southeast region and the Middle Yangtze River region have the highest efficiency values, reaching 1.09, while the northwest region ranks last with an average efficiency value of 0.66. Shanghai performs the best, while Ningxia performs the worst, with efficiency values of 1.43 and 0.58, respectively; (iii) the provinces with lower efficiency values mainly come from economically underdeveloped remote regions, which can be attributed to issues of water consumption (WC) and energy consumption (EC). Moreover, there are much room for improvement in solid waste emissions (SW) and soot and industrial dust emissions (SD); (iv) the environmental investment, R&D investment, and economic development level can significantly improve GDE, while industrial structure, urbanization level, and energy consumption have inhibiting effects.

Using Shannon Entropy to Improve the Identification of MP-SBM Models with Undesirable Output.

In the context of the COVID-19 global epidemic, it is particularly important to use limited medical resources to improve the systemic control of infectious diseases. There is a situation where a shortage of medical resources and an uneven distribution of resources in China exist. Therefore, it is important to have an accurate understanding of the current status of the healthcare system in China and to improve the efficiency of their infectious disease control methods. In this study, the MP-SBM-Shannon entropy model (modified panel slacks-based measure Shannon entropy model) was proposed and applied to measure the disposal efficiency of the medical institutions responding to public health emergencies (disposal efficiency) in China from 2012 to 2018. First, a P-SBM (panel slacks-based measure) model, with undesirable outputs based on panel data, is given in this paper. This model measures the efficiency of all DMUs based on the same technical frontier and can be used for the dynamic efficiency analysis of panel data. Then, the MP-SBM model is applied to solve the specific efficiency paradox of the P-SBM model caused by the objective data structure. Finally, based on the MP-SBM model, undesirable outputs are considered in the original efficiency matrix alignment combination for the deficiencies of the existing Shannon entropy-DEA model. The comparative analysis shows that the MP-SBM-Shannon model not only solves the problem of the efficiency paradox of the P-SBM model but also improves the MP-SBM model identification ability and provides a complete ranking with certain advantages. The results of the study show that the disposal efficiency of the medical institutions responding to public health emergencies in China shows an upward trend, but the average combined efficiency is less than 0.47. Therefore, there is still much room for improvement in the efficiency of infectious disease prevention and control in China. It is found that the staffing problem within the Center for Disease Control and the health supervision office are two stumbling blocks.