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This study explores the influencing factors on intelligent transformation and upgrading of China's logistics firms under smart logistics, and designs the corresponding framework to guide the practice of firms. By analyzing the characteristics of smart logistics and the transformation and upgrading needs of traditional logistics, from the micro perspective of logistics firms, this paper constructs influencing factor index system of smart transformation and development from four dimensions: logistics technology innovation, logistics big data sharing, logistics management upgrading and logistics decision-making transformation. Logistics firms are divided into firms with medium scale and above and small and medium-sized firms according to their scale. Then EWIF-AHP model is proposed to measure the weight of index system and score the decision-making, so as to evaluate the impact of various influencing factors on transformation and development of logistics firms. The results show that, for logistics firms above medium scale, logistics technology innovation and logistics big data sharing have the most significant impact on transformation and development, followed by logistics management upgrading and logistics decision-making transformation. For small and medium-sized logistics firms, the biggest factor is the upgrading of logistics management, followed by the upgrading of logistics technology, which is almost as important as the influencing factors of the upgrading of logistics management, and followed by the sharing of logistics big data and the transformation of logistics decision-making. Therefore, corresponding countermeasures and suggestions for intelligent transformation of logistics firms have been put forward. [ABSTRACT FROM AUTHOR]

With the rapid development of China’s economy, the electricity load continues to increase, the national demand for power engineering projects is also increasing.In the context of the gradual improvement of national requirements for substation projects, decision makers no longer only consider the optimal standards of project duration, cost and quality, but also the resources consumed in the construction and the degree of impact on the environment are important criteria for judging projects.However, in order to be environment-friendly and based on resource constraints, the project management of substation projects is becoming more and more complicated.In this paper, resource factors are added on the basis of the three classical indexes, and the optimal resource allocation of the project is realized under the condition of minimizing the adverse impact on the environment. The feasibility scheme of multi-objective optimization is obtained through particle swarm optimization algorithm.