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Optimization of Empty Container Repositioning in Liner Shipping

机译:划线运输中空容器重新定位的优化

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Empty container repositioning (ECR), which arises due to imbalances in world trade, causes extra costs for the container liner carrier companies. Therefore, one of the main objectives of all liner carriers is to reduce ECR costs. Since ECR decisions involve too many parameters, constraints and variables, the plans based on real-life experiences cannot be effective and are very costly. For this purpose, this study introduces two mathematical programming models in order to make ECR plans faster, more efficient and at the lowest cost. The first mathematical programming model developed in this study is a mixed-integer linear programming (MILP) model and the second mathematical programming model is a scenario-based stochastic programming (SP) model, which minimize the total ECR costs. Unlike the deterministic model, the SP model takes into account the uncertainty in container demand. Both models have been tested with real data taken from a liner carrier company. The numerical results showed that, in a reasonable computational time, both models provide better results than real-life applications of the liner carrier company.
机译:由于世界贸易不平衡而产生的空集装箱重新定位(ECR)导致集装箱班轮公司公司的额外费用。因此,所有衬里运营商的主要目标之一是降低ECR成本。由于ECR决策涉及太多的参数,约束和变量,因此基于现实生活经验的计划不能有效,并且非常昂贵。为此目的,本研究介绍了两种数学编程模型,以便更快,更高效,成本更高,更高效地制作ECR计划。本研究中开发的第一个数学编程模型是混合整数线性编程(MILP)模型,第二个数学编程模型是一种基于场景的随机编程(SP)模型,最大限度地减少了ECR成本的总成本。与确定性模型不同,SP模型考虑了容器需求的不确定性。两种模型都已通过从班轮运营商公司获取的真实数据进行测试。数值结果表明,在合理的计算时间中,两种模型都比班轮运营商公司的现实生活应用提供了更好的结果。

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