铁路空车调配问题理论模型与方法研究综述OA

Railway empty wagon allocation is a core link of freight organization and directly affects transportation efficiency and operational costs.Based on the"problem-model-algorithm"three-dimensional framework,this paper systematically reviewed the research progress in this field.The results indicate that empty wagon allocation is mainly influenced by three key factors,including characteristics of transportation network structure,demand uncertainty,and operational cost structure.These factors interact nonlinearly,resulting in decreased wagon utilization.In terms of theoretical models,deterministic allocation adopts classical models such as linear programming,while uncertain allocation employs methods including stochastic programming,fuzzy programming,and robust optimization.Specifically,collaborative optimization models such as the"empty wagon-loaded wagon-train service"three-layer service network provide new perspectives for improving allocation accuracy.At the algorithmic level,traditional optimization algorithms are applicable to small-scale railway networks,while hybrid intelligent optimization algorithms demonstrate significant advantages in solving large-scale problems.However,existing studies still have limitations,including insufficient research on uncertainty,imperfect multi-agent collaborative optimization mechanisms,and incomplete carbon accounting systems.Future research should focus on making breakthroughs in robust optimization-based methods for addressing uncertainty in empty wagon allocation,multi-objective collaborative optimization technologies,and green and low-carbon scheduling strategies,thereby facilitating the evolution of railway empty wagon allocation systems toward sustainable development,collaborative operation,and intelligent decision-making.