Optimization of marshalling yard scheduling based on a hybrid intelligent algorithm

Marshalling station is an important production unit in the railway freight system, and also an important node to ensure the efficiency of freight hub and mainline transportation. This paper addresses the problem of resource allocation in marshalling yards. The state of various yard resources in the marshalling station is described from the perspective of the constraint characteristics of time resources and space resources. A scheduling optimization model is developed, and a hybrid intelligent optimization algorithm is proposed to effectively solve the problem. With the same number of iterations, the hybrid salp swarm algorithm outperforms other single heuristic algorithms, achieving time reductions of 16, 36, and 45 minutes in resource consumption respectively. The comprehensive comparison of algorithm performance indicates that our hybrid intelligent optimization approach delivers measurable improvements in both operational efficiency and scheduling quality for railway marshalling yard management.