Optimization of logistics intermodal scheduling model based on counting and efficiency in the context of low carbon economy

Abstract

Abstract It is of great significance to study how to reasonably allocate materials and optimize distribution routes in the context of a low-carbon economy to improve the efficiency of logistics work. This paper constructs a low-carbon economy logistics intermodal dispatch optimization model on the basis of the counting and efficiency model. It carries out the optimization of transport routes under the consideration of logistics transportation externality cost. Its total generalized transportation cost is minimized as the goal of optimization modeling, establishing the cargo transportation operation flow, and outputting the logistics flow distribution and path optimization scheme under the whole integrated transportation network. The multimodal transportation optimization model is solved by using triangular fuzzy theory to select the optimal scheduling scheme, and simulation analysis is carried out using an earthquake-stricken area as an example. The results show that the comprehensive satisfaction degree of the disaster victims of the rescue plan obtained by the proposed intermodal logistics scheduling optimization model is 0.9022. At the same time, the value of GAP obtained by this paper’s method for optimization in a multi-scenario deterministic environment is smaller than that of the traditional method by 0.002~0.068, and the running time of this paper’s method is less than that of the conventional algorithm by 81.9~1400.5 s. The study verifies the validity of the proposed intermodal logistics scheduling model and is useful for improving logistics dispatching and path optimization. The study confirms the effectiveness of the model proposed in this paper, which has some applications and promotion potential for improving logistics deployment and other auxiliary decision-making.