仿真建模海洋货柜码头开发--Paper代写范文

Paper代写范文:“仿真建模海洋货柜码头开发”，这篇论文主要描述的是近几年来世界贸易呈现出稳定的发展趋势，港口货柜码头的集装箱数量在快速的增加，如何提高码头集装箱的处理性能是每一个货柜码头面临的难题，本文提出通过仿真建模的方式，研究货柜码头如何节约成本和提高性能。

The world trade has shown a stable increase over the previous years and this trend still continues. With a growing container turnover, increasing container terminal performance is a critical issue for the container terminals. At the same time, high operating costs for ships and container terminals and also high capitalization of ships, containers and port equipment demand a reduction of unproductive times at port.  Therefore, the potential for cost savings is high and importance of performance analysis tools is becoming more acute with increasing container flows.

For increasing efficiency there exist different methods of modeling and simulation models. A general disadvantage of these models is insufficient detailing of micro-operations and involved resources which limit possibility of estimating effect of a specific resource unit on the overall productivity of the logistics chain of the terminal. Therefore, the problem of estimating efficiency of specific resources in conditions of random resource interaction still largely remains unaddressed.

Filling in this gap, the promotional work presents an original developed methodology for simulation modeling of marine container terminals. Specifically, the following major points of the research represent scientific innovation:  

- there has been created a micro-simulation model of Baltic Container Terminal at predefined level of detailing (up to single resource unit with second-wise monitoring possibilities). The created mode l represents a unique marine container terminal micro-simulation model in terms of depth of detailing and visualization. 

- the paper represents an efficient approach for choosing a rational level of detailing through top-to-bottom hierarchically integrated simulation models. The outlined methodology allows multiple levels of detailing. The approach is presented in 2.2.1. Hierarchically integrated BCT models. 

- the model features input adjustable input generators (generators of container flow). The easily adjustable generators are important for ‘what if…?’ scenario analysis for analyzing potential bottlenecks in terminal performance for container flow characteristics differing from the historical data. For the aims set out in this work, the input generators were adjusted for the historical data of BCT. 

- practical application of the developed simulation model represents a new approach developed in the research for choosing an optimal combination of resources which yields more reliable results than the traditional method. Several applications of the approach are presented in CHAPTER 3.   Practical applications of simulation model.   One of the important aspects of the described simulation is its wide range of applications for performance and cost-efficiency analysis.

Namely, there have been addressed the following issues:

- determining the optimal size of truck workgroups for the Baltic Container Terminal,  

- researching effect of yard location proximity to the berths and the number of trucks on net productivity 

- determining historical resource operational cycle times basing on BCT database data. There has been performed a sensitivity analysis of the solutions obtained which revealed reasonable model stability with regard to input variations in productivity values.

- among combinations of three available quay cranes, three yard cranes, and brigade of three to six trucks with unique performance and costs there was chosen a single optimal cost/performance combination of  resources using the simulation model.  

It has been demonstrated that the thoroughly developed logistical model of specific operations affected by random fluctuations allows determination of basic technological and economic data as well as allows quantitative estimation of the associated economic and technological risks of the modeled operations. The simulation model is used by management of the Baltic Container Terminal as decision-support and personnel training tool for workload planning.

Finally, thanks to the logical block-based structure of the model, the underlying principles and methodology can easily be transferred to general terminal and warehousing systems modeling (such as industrial or passenger airports, marine, or railway terminals) and diverse resource mining facilities. This represents solid foundation for future research and application of modeling methodology for the mentioned types of objects.

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