混合不确定条件下多式联运路径优化

Optimization of multimodal transportation routes under mixed uncertainties

针对运输时间及需求不确定的多式联运路径优化问题,综合考虑货运过程中节点作业时间窗、运输方式固定出发时刻及终点处的收货时间窗约束,采用基于情景的鲁棒优化方法,建立以运输、中转和仓储费用之和最小的多式联运路径优化模型,设计遗传算法并进行有效性检验.通过算例研究比较不同模式下多式联运的运输方案及成本,并探究鲁棒优化解的质量与遗憾系数、随机数波动范围的关系.研究结果表明:节点时间窗的存在和改变会导致运输成本和运输方案的变化,混合不确定条件下的多式联运路径鲁棒优化受到遗憾值约束及不确定因素波动范围的影响,将导致运输成本增加.由此,多式联运决策者需预判不确定因素的影响、选择合适的最大遗憾值、关注节点混合时间窗约束以降低成本提高效率.

Addressing the optimization of multimodal transportation routes under uncertain transporta-tion time and demand,a scenario-based robust approach is employed to establish an optimized multi-modal transportation routes model that minimizes the combined expenses of transportation,transship-ment,and warehousing.In this model,constraints such as node operation time windows,fixed depar-ture times for transportation modes,and time windows for receiving at the destination are considered comprehensively.A genetic algorithm is designed and validated for effectiveness.Through case stud-ies,the paper compares transportation plans and costs for multimodal transport under different sce-narios,investigating the relationship between the quality of robust optimization solutions,regret coeffi-cients,and the fluctuation ranges of random numbers.Results indicate that the presence and alteration of node time windows lead to the change of transportation costs and transportation schemes.The ro bust optimization of multimodal transportation paths under mixed uncertainty is impacted by the regret coefficient constraint and the fluctuation range of uncertain factors,resulting in increased transporta-tion costs.Therefore,decision makers in multimodal transportation should anticipate the impact of un-certain factors,choose suitable maximum regret values,and focus on mixed time window constraints at nodes to reduce costs and improve efficiency.