集装箱铁路运输物流多目标函数优化及降本增效研究

Multi-objective function optimization and cost reduction and efficiency increase of container railway transportation logistics

建立集装箱铁路运输物流多目标函数模型,是为实现其物流总成本最优化奠定理论基础。通过问题界定、模型假设、建立多目标函数模型及约束条件,结合具体案例进行实证分析,并运用遗传算法对模型求解。结果表明:每单位集装箱铁路货源运输系统的总成本比优化前的总成本要低,多目标函数优化客观阐释了供应链物流的服务对象、货运站场业务办理的区位分布、路径和布局总量,验证了多目标函数模型的正确性和有效性。根据研究结论,提出相关对策建议。

The establishment of a multi-objective function model of container railway transportation logistics is to lay a theoretical foundation for the optimization of its total logistics cost.Through problem definition,model assumptions,the establishment of multi-objective function models and constraints,this paper used the empirical analysis and the genetic algorithms with specific cases to solve the model.The results show that the total cost of per unit of the container railway cargo transportation system is lower than the total cost before optimization.Multi-objective function optimization objectively explains the service objects of supply chain logistics,the location distribution of freight station business,the total number of paths and layouts,and verifies the correctness and effectiveness of the multi-objective function model.According to the research conclusion,this paper put forward the relevant countermeasures and suggestions.