This paper proposes a collaborative optimization strategy for multiperiod procurement and multimodal transportation that considers cost factors such as procurement, transportation, transshipment, and storage costs incurred for early arrival. A mixed-integer planning model is established to minimize the overall operating costs of cross-border e-commerce enterprises by arranging procurement, transportation, and storage strategies. Considering the fluctuation of procurement costs with the market environment, this study constructs robust optimization models and develops linear robust equivalence models through mathematical transformation to improve the efficiency of problem solving. A hybrid heuristic algorithm, KIGALNS, is proposed to solve this problem. Finally, a series of numerical experiments are conducted to show that our robust model can better address multimodal transportation path optimization problems such as procurement cost uncertainty. In addition, the correctness of the proposed model and the effectiveness of the algorithm and collaborative optimization strategy were verified. Finally, the case analysis shows that the early procurement strategy helps reduce total operating costs, and the robust model can effectively handle multimodal transportation path optimization problems such as uncertain procurement costs. While promoting cost reduction and efficiency improvement in transportation, the proposed approach comprehensively considers the impact of procurement plans and uncertain factors, providing theoretical guidance and scientific solutions for joint decision-making in enterprise procurement transportation.

中文翻译：

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在不确定的环境中为多周期多式联运提供稳健的采购和路线策略优化

本文提出了一种多期采购和多式联运的协同优化策略，该策略考虑了提前到达产生的采购、运输、转运和存储成本等成本因素。建立混合整数规划模型，通过安排采购、运输、仓储策略，最大限度地降低跨境电商企业的整体运营成本。考虑到采购成本随市场环境的波动，本研究构建了稳健优化模型，并通过数学变换开发了线性稳健等价模型，以提高问题解决效率。提出了一种混合启发式算法 KIGALNS 来解决这个问题。最后，进行了一系列数值实验，表明我们的鲁棒模型可以更好地解决采购成本不确定性等多式联运路径优化问题。此外，还验证了所提模型的正确性以及算法和协同优化策略的有效性。最后，案例分析表明，早期采购策略有助于降低总运营成本，鲁棒模型可以有效处理采购成本不确定等多式联运路径优化问题。所提方法在促进运输降本增效的同时，综合考虑采购计划的影响和不确定因素，为企业采购运输的联合决策提供理论指导和科学解决方案。