Optimization of the Sino-Europe Transport Networks Under Uncertain Demand

Qing Nie, Songyun Liu, Qiyu Qian, Zheyi Tan, Huiwen Wang
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引用次数: 4

Abstract

This paper studies a consolidation center selection and cargo transportation optimization problem of the Sino-Europe railway express. It takes account of demand uncertainty and multiple cost factors, such as transportation cost, time cost, waiting cost before consolidation, penalty cost of not full load after distribution, track changing cost, and customs clearance fee. A complicated mixed-integer programming (MIP) model is presented to describe the problem. Then a solution method based on binary particle swarm optimization (BPSO) is designed to solve the model of different scales of cases. Extensive numerical experiments generated from real-world data are conducted to validate the effectiveness of the proposed model. Moreover, we compare the efficiency of the solution method with a commercial solver and a heuristic algorithm based on variable neighborhood search (VNS). Results show that our solution method can optimally solve the problem in small-scale cases and get near-optimal solutions for large-scale problem instances. The proposed mathematical model and the calculation results may provide valuable insights for both business owners and government.
需求不确定条件下的中欧交通网络优化研究
本文研究了中欧班列集散中心选择与货物运输优化问题。它考虑了需求的不确定性和多重成本因素,如运输成本、时间成本、拼箱前的等待成本、配送后未满载的惩罚成本、跟踪变更成本、清关费用等。提出了一个复杂的混合整数规划模型来描述这一问题。在此基础上,设计了一种基于二元粒子群优化(BPSO)的求解方法来求解不同尺度的案例模型。从实际数据生成的大量数值实验进行了验证所提出的模型的有效性。此外,我们还将该方法的求解效率与商业求解器和基于可变邻域搜索(VNS)的启发式算法进行了比较。结果表明,所提出的求解方法在小规模情况下能得到最优解,在大规模情况下能得到近似最优解。所提出的数学模型和计算结果可能为企业主和政府提供有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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