港口航運(yùn)物流管理中集裝箱調(diào)配的分布式魯棒優(yōu)化研究
[Abstract]:In the past 20 years, driven by the policy of reform and opening up, China's national economy and foreign trade have developed rapidly. Containers have been more and more widely used in the transport of all kinds of goods because of their advantages of convenience, rapidity, firmness and convenience for multimodal transport. But at the same time, the use of containers is also facing the challenge of trade imbalance between countries and regions. This has led to the accumulation of a lot of empty boxes in import-led ports, while export-oriented ports urgently need a large number of empty boxes. This makes shipping companies have to transport a large number of empty containers between ports, and the deployment of empty containers is a huge operating cost for shipping companies. Therefore, solving the problem of empty container allocation can help shipping companies reduce costs and help to form the competitiveness of enterprises. In this thesis, the problem of empty container allocation is studied by using distributed robust optimization, and the collapsible container is introduced innovatively. The standard containers discussed in this thesis are all 20 feet. The foldable containers are exactly the same as the standard containers when they are opened, and the volume of the standard containers is 1/4 of that of the standard containers at the time of folding. Collapsible containers can not only save storage space, but also save space, which means that the inventory cost will be greatly reduced and the container loading capacity of ships will be increased. Secondly, foldable containers can also improve loading and unloading efficiency. For the container allocation problem, firstly, the deterministic model of container allocation problem is established. Secondly, based on the deterministic model, we establish a two-stage stochastic programming model and a distributed robust optimization model when container supply and demand are uncertain. The distributed robust optimization model is transformed into a solvable second-order cone programming model. Finally, we use the rolling time domain simulation method to compare the three models, and show that the distributed robust optimization model has more advantages in solving the container allocation problem, and can reduce more costs for enterprises.
【學(xué)位授予單位】:東南大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:F552;F252
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