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An optimisation framework for yard planning in a container terminal: case with automated rail-mounted gantry cranes

机译:集装箱码头堆场规划的优化框架:带有自动轨道式龙门吊的案例

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摘要

Different terminals, with their unique combinations of liner services, yard layouts and equipment configurations, may find that different yard planning strategies work better for their scenarios. While an optimum yard plan can be found for each yard planning strategy, it is interesting to know which strategy gives the best plan. In designing an IT-based search engine to discover the best yard planning strategy and/or scenario, having a generic specification and solver is important, so that the whole solution space could be represented and searched. We design a generic problem specification with parameterised scenarios and yard planning strategies, and formulate a generic mathematical model that solves for the optimum weekly yard plan template for that given problem. A good run time of this generic model is extremely important as the model will be executed hundreds of times in the search engine. Experiments are conducted with the model. An interesting discovery is that re-modelling a set of integer variables into multiple binary variables improve the run time tremendously, and in some cases, outperform the relaxed original model. We also find that the strategy which allows sharing of yard space between services yield better utilization for yard space and rail mounted gantry handling capacity.
机译:不同的码头,加上班轮服务,堆场布局和设备配置的独特组合,可能会发现不同的堆场规划策略更适合其方案。尽管可以为每个院子规划策略找到一个最佳院子计划,但有趣的是要知道哪种策略可以提供最佳计划。在设计基于IT的搜索引擎以发现最佳的院子规划策略和/或方案时,具有通用的规范和求解器很重要,因此可以表示和搜索整个解决方案空间。我们设计了具有参数化方案和院子规划策略的通用问题规范,并制定了通用数学模型来求解给定问题的最佳每周院子规划模板。这个通用模型的良好运行时间非常重要,因为该模型将在搜索引擎中执行数百次。用该模型进行实验。一个有趣的发现是,将一组整数变量重新建模为多个二进制变量可极大地改善运行时间,并且在某些情况下,其性能优于宽松的原始模型。我们还发现,允许在服务之间共享堆场空间的策略可更好地利用堆场空间和轨道式龙门架搬运能力。

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