Optimization of multi-objective flexible scheduling for container rail mounted gantry cranes in railway logistics yards.

Abstract

With the advancement of multimodal transport systems, railway logistics terminals have become critical hubs connecting different transport modes, and the efficiency of rail-mounted gantry crane (RMG) operations directly affects train handling performance. This study develops a revised multi-objective scheduling framework for flexible RMG operations in railway container terminals. The model considers three coordinated criteria: total completion time, workload balance among RMGs, and path-interference prevention under dynamic safety-distance requirements. To improve practical solvability, the framework combines resource enumeration, initial crane layout optimization, and an improved genetic algorithm with adaptive operators and tabu-search-based local refinement. In the Xi'an International Port Station case with 110 container tasks and five RMGs, the proposed IGA obtained an average completion time of 752.4 min under the baseline configuration and remained feasible under tested safety-distance and crane-number scenarios. The results indicate that integrating initial layout decisions with flexible task assignment can improve schedule quality in the tested case. The claims are limited to the reported instance, and the method is presented as a reproducible heuristic rather than a proof of global optimality.