In order to address the lack of collaborative decision and failure to notice the emergency and fairness of relief after disasters have occurred, a collaborative decision-making system for emergency relief materials dispatching is established. According to the forecast of the demand for postdisaster relief materials, the entropy weight-TOPSIS method is applied to measure the urgency of the disaster area; then, a “Hub-and-Spoke” dispatching network is constructed. In this paper, a multiobjective collaborative relief material dispatching model is built, which has great performance in terms of minimal distribution cost and maximal fairness, and the objective of fairness requires minimizing the penalty cost caused by unsatisfied demands. Based on the urgency of demand points, the simulated annealing algorithm is designed to solve the Pareto disaggregation of multiobjective optimization model. The performance of the model is verified with the case of Wenchuan Earthquake. The results indicate that if the fair distribution of supplies is emphasized, it will increase the number of rescue vehicles and the number of distribution batches. On the other hand, a variety of relief material dispatching plans can be provided based on calculation of the Pareto front for policy-makers.
In order to achieve net zero emissions, the global transportation sector needs to reduce emissions by 90% from 2020 to 2050, and road freight has a significant potential to reduce emissions. In this context, emission reduction paths should be explored for road freight over the fuel life cycle. Based on panel data from 2015 to 2020 in China, China's version of the GREET model was established to evaluate the impact of the crude oil mix, electricity mix, and vehicle technology on China's reduction in road freight emissions. The results show that the import share of China's crude oil has increased from 2015 to 2020, resulting in an increase in the greenhouse gas (GHG) emission intensity of ICETs in the well-to-tank (WTT) stage by 7.3% in 2020 compared with 2015. Second, the share of China's coal-fired electricity in the electricity mix decreased from 2015 to 2020, reducing the GHG emission intensity of battery electric trucks (BETs), which is approximately 6.5% lower in 2020 than in 2015. Third, different vehicle classes and types of BETs and fuel cell electric trucks (FCETs) have different emission reduction effects, and their potential for energy-saving and emission reduction at various stages of the fuel lifecycle are different. In addition, in a comparative study of the vehicle technology, the results show that: (1) for medium-duty truck (MDT) and heavy-duty truck (HDT), FCETs have lower GHG emission intensity than BETs, and replacing diesel-ICETs can significantly reduce GHG emissions from road freight; (2) for light-duty truck (LDT), BETs and FCETs have the highest GHG emission reduction potential; thus, improving technologies such as electricity generation, hydrogen fuel production, hydrogen fuel storage, and transportation will help to improve the emission reduction capabilities of BETs and FCETs. Therefore, policymakers should develop emission standards for road freight based on vehicle class, type, and technology.
With the continuous development of economy currently, the economic exchange between regions has been increasingly frequent and the development scale of domestic and foreign logistics economy is continuously expanding, which, based on the spatial mode and spatial structure, have great effect on the development of logistics economy of China. And the spatial mode has also become the important theoretical basis for the evolution of logistics economy. In combination with the development characteristics of logistics economy and the movement law of spatial logistics economy, the author proposes the theoretical mode appropriate for the development of logistics economy of China, form the spatial operation mode of logistics economy with point-axis-network-plane structure and the joint spatial pattern of driving of the surrounding economic zones by the central developed cities for joint development.
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