Abstract

Railway logistics terminals are crucial nodes in the national logistics system. Prior to the market-oriented reform of railway logistics, the warehousing operations at these stations primarily focused on temporary storage services before and after shipment, making it difficult to provide customers with integrated warehousing and transportation logistics services. With the advancement of railway marketization reforms, railway logistics terminals have gradually begun to offer socialized warehousing services, acquiring the capability to provide integrated warehousing and transportation services. In response to market development needs and the requirements for green development in railway logistics, an optimization design model for obtaining green railway logistics solutions is established, considering factors such as carbon emission costs, integrated warehousing and transportation logistics service costs, fuzzy constraints on logistics network capability, transportation time windows and the customer’s risk tolerance level. The model takes minimizing carbon emission costs and railway logistics service costs as dual-objective functions and uses a standardized weighting method to convert the dual-objective functions into a single-objective function for solving using triangular fuzzy numbers to characterize the ability constraints of network nodes, making the model more realistic. This model aims to minimize these costs and assesses the impact of factors such as changes in delivery time limits, shipment quantity, shipment batches, the superposition of multiple goods batches and customer preferences on the railway logistics solution for different scenarios. Research indicates that reasonably designing delivery time limits and aligning shipment times with railway transportation time windows can effectively reduce carbon emissions and logistics costs, and the risk tolerance level has a significant impact on the reliability of railway logistics solutions.

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